Open Access Sources Research Articles

(033) Artificial Intelligence ChatGPT and GPT4 Performance on Male and Female Sexual Dysfunction, Sexually Transmitted Infection, and Male Factor Infertility in the 2019 to 2023 American Urological Association Self-Assessment Study Programs

Abstract Introduction Large Language Model (LLM) applications in Medicine are increasing. Chatbots ChatGPT and GPT4 were tested against medical exams. The vetting of these tests as a source of information for both the patient and physician is needed. A credible source of medical information may be used as the gold standard against which the LLM can be tested. Objective We assess the performance of ChatGPT and GPT4 to answer the American Urological Association (AUA) Self-Assessment Study Program (SASP) questions on male sexual dysfunction (MSD), female sexual dysfunction (FSD), sexually transmitted infection (STI), and male factor infertility (MFI). We aim to find out how credible this LLM is as a source of medical advice. Methods Four registered users of the SASP identified the questions using open book mode in tests from 2019 to 2023, spanning their subscriptions. The questions were ranked for difficulty on a five-point Likert scale. OpenAI ChatGPT 3.5 and GPT4 were used to answer the questions. The GPT program was set to turn off chat history. No plug-ins or feedback were permitted. Prompts were generated from question stems masking question ID and adding the phrase "I am a urologist preparing for my board exam. Please answer the following question:" Images were deleted from questions and substituted with a brief description. All questions were answered separately, first using GPT-4 and then ChatGPT. Three consecutive responses were generated for each prompt, and the consensus answer was tallied. Answers were compared between GPT and provided answer key of SASP. Descriptive statistics, chi-Pearson Chi-square, and Fisher's exact tests were applied. Results We identified 115 questions in the domains of sexual dysfunction, STI, and MFI. Only one question had an associated image. GPT4 performed better than ChatGPT in all domains, providing correct answers of 60% versus 40% (p=0.000). A total of 89.9% of correct answers were three times unanimously regenerated by GPT4 (p=0.007) and 67.4% by ChatGPT (p=0.244). Within each domain, there was no significant difference in the correct answers for each chatbot (Table-1) or test year (p=0.682). The SASP source reference answers were Campbell's Urology only in 38.3 %, AUA guidelines only in 17.4%, AUA core curriculum only in 10.4%, and combinations with other sources in 33.9%. There was no significant association of source reference with the correct answers of GPT4 (p=0.058) or ChatGPT (p=0.451). Only 19.1% were open-access sources, 20% were partially open-access, and 60.9% were restricted to subscribers. The availability of the source did not significantly affect the correct answers of GPT4 (p=0.272) or ChatGPT (p=0.231). Both chatbots' correct answers were associated significantly with easier questions (Table-2). Conclusions The LLM tested has an average accuracy as a source of credible medical information on Sexual dysfunction, STI, and MFI. GPT4 performs better than ChatGPT, especially when there is a unanimous regenerated response. The development of a better model to serve a broader group of physicians and patients will require training of the chatbot on credible urology literature that includes the currently 81% restricted sources. Disclosure No.

Toward coordinated planning and hierarchical optimization control for highly redundant mobile manipulator

This paper represents a constraint planning and optimization control scheme for a highly redundant mobile manipulator considering a complex indoor environment. Compared with the traditional optimization solution of a redundant manipulator, infinity norm and slack variable are additionally introduced and leveraged by the optimization algorithm. The former takes into account the joint limits effectively by considering individual joint velocities and the latter relaxes the equality constraint by decreasing the infeasible solution area. By using derived kinematic equations, the tracking control problem is expressed as an optimization problem and converted into a new quadratic programming (QP) problem. To address the optimization problem, the two-timescale recurrent neural networks optimization scheme is proposed and tested with a 9 DOFs nonholonomic mobile-based manipulator. Additionally, the BI2RRT∗ path-planning algorithm incorporates path planning in the complex environment where different obstacles are positioned. To test and evaluate the proposed optimization scheme, both predefined and generated paths are tested in the Neurorobotics Platform (NRP) 22https://neurorobotics.net.which is open access and open source integrative simulation framework powered by Gazebo and developed by our team.

DeepReality: An open source framework to develop AI-based augmented reality applications

Augmented reality (AR) and Artificial Intelligence (AI) are technologies pioneers in innovation and alteration in several domains. AR allows the creation of an entirely new and interactive experience for users. However, there are several drawbacks in developing AR applications, such as the marker identification process and the creation of content itself. These are very time-consuming procedures and require ad-hoc development. The advantages of using AI to solve AR limitations have recently been explored in literature. Motivated by these findings, in this paper it is proposed DeepReality, a software toolkit plug-in for Unity 3D. It is conceived for allowing developers to integrate any Deep Learning (DL) models into Unity, through AR Foundation and Barracuda inference engine. DeepReality is aimed at simplifying and streamlining the usage of DL models in conjunction with AR. As such, users skilled in Unity and DL can easily create mobile applications (iOS and Android) to: extract visual features of real-world objects (framed with the device camera) via DL; Show on-screen content on top of those real-world objects, via AR. DeepReality performs object semantic processing within the scene, and extended semantic effects for incongruent objects, overcoming the environmental tracking, which is feature-based. In order to test DeepReality usability, experiments have been performed on the execution time and memory usage data, demonstrating the feasibility and possibility of integrating and using DNNs models in mobile applications for AR. The complexity analysis confirms that DeepReality can be completely executed on mobile devices. DeepReality is also open-source and it is freely available in the Unity asset store. By fostering accessible AI-AR integration, DeepReality addresses key shortcomings in existing approaches, encapsulating contributions such as versatile DL integration, open-source accessibility, operational validation, and comprehensive metrics analysis. DeepReality empowers developers to transcend boundaries, enriching AR applications with AI’s transformative potential. Our proposed framework fosters benchmarking, comparison, and a future harmonised by AR-AI synergy.

My Best Alaskan Life: Addressing Adolescent Mental and Reproductive Health in Alaska.

Since 2020, a multisector research team has coordinated a youth-driven, community-based participatory research project to adapt a reproductive life plan for application in a statewide initiative called My Best Alaskan Life (MBAL). The RLP is adapted for Alaskan youth and is intended to support teens in decision-making processes reflecting cultural priorities, personal goals, and sexual and reproductive health. Background. With 46% of youth in Alaska reporting not having used a condom during their last sexual intercourse and 15% not having used contraception, unintended pregnancy and transmission of STIs will continue. Furthermore, Alaskan youth also cite high rates of hopelessness and suicidality, and research shows that poor mental health among adolescents is correlated with developing and maintaining high-risk sexual behaviors. An intervention focusing on supporting mental wellness and developing personal goals in the context of sexual health decision-making may encourage adolescents to adopt safer sexual health behaviors. The MBAL research team completed a statewide pilot assessing the design and implementation of the tool, gathering feedback from over 700 survey responses (youth, ages 14-20); conducted 10 in-depth interviews (adult partners at community organizations and clinics); and hosted two youth-led design review sessions. Questionnaire respondents were overwhelmingly positive about the tool (91% "liked or loved" the tool) and its potential applicability in their community (86% cited "very applicable"). Project next steps include incorporating design recommendations, a statewide randomized control trial and ultimately, open source access for all interested parties.

Modeling the freezing process of aqueous solutions considering thermal gradients and stochastic ice nucleation

Despite its importance to multiple scientific fields and industries, the freezing process of aqueous solutions is not yet completely understood. In particular, the relationship between temperature gradients within a solution and the occurrence of stochastic ice nucleation remains elusive. To address this knowledge gap, we have derived a novel stochastic spatial freezing model from first principles. The model predicts with quantitative accuracy how temperature gradients affect the stochastic ice nucleation of sucrose solutions in vials. This motivated a detailed study of the freezing-stage in freeze-drying, revealing that a broad range of temperatures are present at the time of nucleation at different positions within the vial. This must be considered when interpreting experimental studies that measure the temperature only at a single point with a thermocouple. To ensure that both researchers and practitioners benefit from this modeling work, we provide open source access to it within our python package ethz-snow.

Quality of YouTube Videos Regarding Anterior Cruciate Ligament Reconstruction Using Quadriceps Tendon Autograft Is Unsatisfactory

PurposeThis study aimed to assess the validity and informational value of teaching material regarding anterior cruciate ligament reconstruction (ACL-R) using quadriceps tendon (QT) autograft provided on the YouTubeTM video platform. MethodsAn extensive systematic search of the YouTubeTM video platform was performed, and all videos that met the criteria were included in the analysis. The analysis of the video content was performed using the DISCERN instrument, Journal of American Medical Association (JAMA) benchmark criteria and Global Quality Score (GQS). The duration of the videos, the date of publication, and the number of likes and views were recorded. Furthermore, videos were categorized based on the source (physicians, companies, patients), the subject (surgical technique, patient experience and overview [overview videos were videos in which multiple aspects were analyzed]) and the type of content (educational or subjective patient experience). ResultsA total of 88 videos were included in the analysis. Seventy-one (80.7%) videos were published by physicians, 15 (17.0%) by patients and 2 (2.3%) by companies. The majority of the videos described various surgical techniques (59 – 67.0%), 80.7% of the videos (72 – 81.8%) had an educational nature, and the remaining 18.2% described patient experiences. The mean length of the videos was 8.21 ±7.88 minutes. The mean number of views was 3988.51 ±9792.98 (range: 9-56047), while the mean numbers of comments and likes were 30.07±70.07 (range: 0-493) and 4.48 ±14.22 (range: 0-82), respectively. The mean DISCERN score, JAMA score, and GQS were 27.43 ±11.56 (95% CI: 25.01–29.85; range: 17-68), 1.22 ±0.85 (95% CI: 1.04–1.40; range: 0-3), and 1.82 ±0.93 (95% CI: 1.63–2.01; range: 1-4), respectively. For all scores, videos published by physicians had higher quality (DISCERN score, JAMA score, and GQS) (p<0.05). Among all of the analyzed videos, overview videos were of the highest quality (p<0.05). ConclusionsYouTube™ is a fast and open-access source of mass information. The overall quality of the videos on ACL reconstruction performed using QT autograft was unsatisfactory, demonstrating low educational quality and reliability. Currently, YouTube™ cannot be recommended as a reliable source of information on ACL reconstruction with the quadriceps tendon.

Trust Building in Public Health Approaches: The Importance of a "People-Centered" Concept in Crisis Response.

To argue for trust-building as a key solution for responding to public health crises in the face of political ambiguity in international health governance. This perspective piece reviews fundamental concepts and discusses future directions using secondary data from open-access sources. The promise of learning from Covid-19 and previous public health crises, along with the growing recognition of a 'Health For All Policies' approach, clash with siloed preparations, management, and recovery plans for future emergency crises. Trust is proposed as a possible solution to overcome these limitations. It acts as a binding force that unites individuals within the community, fostering a sense of belonging and participation. Trust-building is viewed as a "People-Centered" approach in Crisis Response, aimed at creating active and resilient communities to foster preparation and readiness, respond to emergent risks, facilitate recovery, and mitigate risks. A remaining question is how to measure and identify the dimensions and determinants of trust in specific circumstances. Some ideas are systematized to highlight the pathway to build trust in public health approaches, including transparency, education, robust and equitable health systems, strengthened social capital, stakeholders' engagement, and health workforce training. Trust in public health approaches can be fostered through consistent delivery of quality care, a clear, shared vision, and values underpinned by ethical standards. It requires a commitment to stakeholder well-being, including staff, and the integration of reliability, integrity, and transparency into policies, strategies, and practices. Exemplary leadership, openness in resource utilization, addressing waste or corruption, and effective communication of these principles are essential.

Diversity and Abundance of Edible Wild Fruit and Leaf Plants in Parts of Forest and Savanna Eco-regions, Nigeria.

Wild foods are important sources of nutrition for one out of six people worldwide and it remains an open access source of food and income, especially to vulnerable group such as the resource-poor and malnourished children. Different ecological zones in Nigeria are endowed with diverse edible fruits and leaves and hence their diversity and abundance differ. With the previous and current rate of deforestation particularly in the African continent and specifically in Nigeria, the diversity and abundance of these invaluable forests –derived foods across the forest and savanna ecozones in Nigeria are unknown. An inventory of forest-derived edible fruits and leaves was conducted using a systematic line transect in two (2) selected forest reserves in each ecological zone. Five line transects of 515 m in length, with a distance of at least 150 m between two parallel transects was used. Five sample plots of 25 m x25 m in size were laid in alternate position along each transect at 100 m interval. A total of 25 sample plots were laid in each of the selected forest reserves. In each sample plot, all edible fruits and leaves encountered were identified and their frequency recorded. The frequency of the species per ha was used to compute the relative species abundance and Shannon weiner diversity index. The species diversity across the ecological zones was compared using one-way analysis of variance. Shannon-weiner diversity index (3.49) for the rainforest edible wild fruits and leaves is significantly higher (P≤ 0.05) than in all the other ecological zones. This is followed by Guinea savanna (3.10), Derived savanna (3.02), Sudan savanna (2.91), and Sahel savanna (2.83) while the mangrove forest has the lowest diversity index (2.53). Assessing species diversity helps in understanding the resilience of forest ecosystems. This knowledge is crucial for fostering environments that can withstand and recover from adverse events. Policy makers rely on scientific studies to design regulations and conservation strategies. This research provided evidence-based insight necessary for informed decision-making to protect forest reserves

KOS (Helper Systems)

This is a critical evaluation of kOS from Helper Systems, a PDF software designed for Mac OS, addressing its marketing strategies, unique features, and potential value proposition. The software claims to streamline PDF manipulation and enhance accessibility, boasting features like improved navigation, data visualization, and AI-driven research tools. However, skepticism is raised regarding its departure from existing solutions and its appeal beyond a niche user base in the arts and design. The integration of AI is questioned, particularly in the absence of open-source accessibility. The review highlights the competitive landscape of PDF software, acknowledging user fatigue and established alternatives like Adobe Acrobat. Despite the software’s promotion of a user-friendly library with subject keyword searching, concerns are raised about its market exclusivity and compatibility with institutions requiring Microsoft usage. Ultimately, the author emphasizes the challenge of standing out in a saturated market and the need for a nuanced assessment of kOS’s ability to justify its learning curve and price point, especially in addressing accessibility standards and workflow challenges in ever-changing digital environments.

Agcounts: An R Package to Calculate ActiGraph Activity Counts From Portable Accelerometers

Portable accelerometers are used to capture physical activity in free-living individuals with the ActiGraph being one of the most widely used device brands in physical activity and health research. Recently, in February 2022, ActiGraph published their activity count algorithm and released a Python package for generating activity counts from raw acceleration data for five generations of ActiGraph devices. The nonproprietary derivation of the ActiGraph count improved the transparency and interpretation of accelerometer device-measured physical activity, but the Python release of the count algorithm does not integrate with packages developed by the physical activity research community using the R Statistical Programming Language. In this technical note, we describe our efforts to create an R-based translation of ActiGraph’s Python package with additional extensions to make data processing easier and faster for end users. We call the resulting R package agcounts and provide an inside look at its key functionalities and extensions while discussing its prospective impacts on collaborative open-source software development in physical behavior research. We recommend that device manufacturers follow ActiGraph’s lead by providing open-source access to their data processing algorithms and encourage physical activity researchers to contribute to the further development and refinement of agcounts and other open-source software.

Dairy farming in Akmola region of the Republic of Kazakhstan: main directions of intensification

The goal is to analyze the current situation on market for milk and dairy products in the Akmola region, to determine trends in sustainable development of dairy cattle breeding in the conditions of innovative economy. Methods – analytical and statistical industry information is systematized and summarized on the basis of economic-statistical, balance sheet, abstractlogical methods from open access sources and scientific literature. Results – the state of the dairy sub-industry in the region is considered. The authors identified the reasons that make it difficult to expand the capabilities of dairy farms. It is shown that highly efficient, resource-saving technologies are of particular importance for the intensification of the production of milk and its processed products and the economic growth of this market segment. The main focus of state support for dairy farming is outlined. To increase its effectiveness, effective republican and regional programs will be implemented. Active work to create modern large dairy farms in the region and raise dairy cattle will become attractive for investment. At dairy food complexes, the productivity of cows significantly increases, gross milk production increases, and optimal conditions for its primary processing are provided, which, in turn, ensures the quality of raw materials. Conclusions - the article proves the relevance of the study, which lies in the proposed measures to further increase the role of dairy farming in achieving food security of the state, justifying the need for public investment, increasing the volume of subsidies (direct subsidies and compensation for interest rates on loans), as well as choosing priority areas (infrastructure, technology) and taking into account many indicators that affect the efficiency of reproduction.

Pristup odozdo prema gore nasuprot odozgo prema dolje: kako se participativni dizajn može koristiti za definiranje postkonfliktnog kulturnog pamćenja u Hrvatskoj

Ethnic tensions and a constitutional crisis brought about the disintegration of Yugoslavia, which resulted in Croatia loosening ties with the Federation and subsequently declaring its independence. The quest for Croatian independence led to the Homeland War which took place between 1991–1995. The post-conflict transformation of the country primarily concentrated on the political and economic aspects of reconstruction, however the importance of developing a national strategy to deal with cultural memory, as part of the rebuilding process, has largely been neglected. Through a series of case studies, this paper will reveal how a significant proportion of Croatia’s cultural memory is dealt with through various forms of community engagement, centering around local civic organisations that “sprung up” as a consequence of the Homeland War. These communities are staging memorials, not just as places and occasions to gather around grief, but as means of highlighting the self-expression of loss in a public setting. Technological advancements, especially open-source access to new media, has encouraged more personal and community initiated and driven projects. Centered around participatory design, these projects demonstrate a more inclusive approach that enables local communities to record, collect and communicate their cultural memory, rather than rely on ‘approved’ state institutions. This article looks at how participatory design can aid in bridging and preservation of cultural memory of the Homeland War through the development of a participatory design framework which could be used as a central reference point to facilitate participatory projects between cultural institutions and their patrons, thus creating a more empowering approach to post-memory.

Europe PMC in 2023.

Europe PMC (https://europepmc.org/) is an open access database of life science journal articles and preprints, which contains over 42 million abstracts and over 9 million full text articles accessible via the website, APIsand bulk download. This publication outlines new developments to the Europe PMC platform since the last database update in 2020 (1) and focuses on five main areas. (i) Improving discoverability, reproducibilityand trust in preprints by indexing new preprint content, enriching preprint metadataand identifying withdrawn and removed preprints. (ii) Enhancing support for text and data mining by expanding the types of annotations provided and developing the Europe PMC Annotations Corpus, which can be used to train machine learning models to increase their accuracy and precision. (iii) Developing the Article Status Monitor tool and email alerts, to notify users about new articles and updates to existing records. (iv) Positioning Europe PMC as an open scholarly infrastructure through increasing the portion of open source core software, improving sustainability and accessibility of the service.

Addressing the challenges in scholarly communication

After twenty years of the open access movement, there has been growth in the uptake of open access, and some progress has been made in achieving its original goals; however, results have been far from satisfactory, with more than half of the research literature still closed (COKI, 2022; Curry, 2018). Moreover, new concerns have arisen, such as questionable quality and the reliability of peer review, in particular predatory publishing. There are also threats to equity, including stratifications of publishing as a consequence of the exclusionary character of the author-pays model of open access, and new risks of bias and exclusion in the means of transparent evaluation (Ross-Hellauer et al., 2022). It is argued that these challenges are the result of the uncritical narratives of openness and their narrow focus on access alone which fail to address inequitable power dynamics, systemic problems and the structural barriers in scholarly publishing and knowledge production (Perry, 2020; ibid.).These cha(lle)nges in the system of scholarly communication, coupled with recent advances in technology and the tectonic transformations in the information environment, require new (pedagogical) approaches and foci that would enable researchers and students to understand and navigate such a complex environment; for this, a holistic and integrative approach to scholarly communication and information literacy is needed (ACRL, 2013; Špiranec, 2015).Scholarly communication, including open access, is impossible without information literacy (Hebrang Grgić, 2016). As they are both concerned with (access to) information, open access and in particular critical information literacy largely share the same goals, ethical dimensions and values of (social and epistemic) justice, equity and democratisation. Indeed, they have been considered instrumental to achieving these, and even proclaimed a panacea and deus ex machina for the current scientific, social and political challenges and crises (Hebrang Grgić, 2016; Kapitzke, 2003). However, literature on the intersections and interplay between open access and information literacy has been limited.This paper seeks to intertwine these two concepts more strongly, for mutual exchange and benefit, by analysing their convergent aspects as well as the role information literacy has in the context of the complexities of the scholarly communication system and in achieving open access. The paper builds on the few empirical studies of the intersections between the two concepts (e.g. Hebrang Grgić (2016) which confirms the importance of ‘open access literacy’), but goes beyond their functional approaches, advocating a more holistic and critical approach to open access to help reinvent it and make a more substantial progress in open access. It argues that the transformations in the information environment and the scholarly communication system require not only basic skills and competences at the core of information literacy but also specific skills of, for instance, managing scientific data and publishing in open access sources. More importantly, what is also required is critical consciousness of all the aspects of the research process including the context, power relationships, and the privileged positions in knowledge production, publishing and dissemination, and an ability to evaluate the quality and reliability of information.The paper proposes critical open access literacy as a pedagogical methodology and strategy to confront the challenges and enable a critical understanding of the contemporary information environment and scholarly communication. In line with the tenets of critical information literacy, critical open access literacy is directed at an analysis and critique of the economic, social, political, legal and technological conditions, aspects and implications of open access and the overall scholarly communication system, as well as the power dynamics, tensions and flaws within them. This will empower students and researchers to navigate this environment successfully and potentially become champions of its transformation to make it more meaningful, reliable, equitable and democratic.

Social responsibility in academic communication

Modern electronic publishing enables faster and easier access to information and scientific publications. Unfortunately, misleading publishing practices have adapted and become harder to identify. It is not only the publication in these journals and publishers that is questionable but also the citation of these sources. We find that such unverified and unreviewed scientific publications can negatively impact the society as a whole.Regrettably, even at the University of Maribor, we are seeing an increase in the use and adoption of such sources. As a result, the University of Maribor Library has compiled a private list of predatory publishers according to our own criteria, we provide further education, create LibGuides, and maintain a public list of open access sources. We also offer advice on checking journals, publishers, and conferences. This includes both students, who should be cautious in the selection and use of sources, as well as lecturers and researchers, who should be careful not just in the selection and use of sources but also in the selection of reputable journals for publication.The very process of submitting the final student theses to the institutional repository includes content similarity detection. Content similarity detection is also available to any University of Maribor researcher who wants to double-check their article before publication. Our practices of raising awareness about unverifiable sources will be presented in more detail on the poster.

Testing the Informativeness of Diverse Measures of Auditory Processing for Clinical Audiological Practice in Middle-Aged Adults in Mexico.

Standard clinical audiologic assessment is limited in its ability to capture variance in self-reported hearing difficulty. Additionally, the costs associated with clinical testing in audiology create financial barriers for hearing health care in developing countries like Mexico. This study used an open-source Spanish-language tool called PART (Portable Automated Rapid Testing) to test the hypothesis that a battery of assessments of auditory processing can complement standard clinical audiological assessment to better capture the variance of self-reported hearing difficulty. Forty-three adults between 40 and 69 years of age were tested in Mexico City using a traditional clinical pure-tone audiogram, cognitive screening, and a battery of PART-based auditory processing assessments including a speech-on-speech competition spatial release from masking task. Results were compared to self-reported hearing difficulty, assessed with a Spanish-language adaptation of the Hearing Handicap Inventory for the Elderly-Screening Version (HHIE-S). Several measures from the PART battery exhibited stronger correlations with self-reported hearing difficulties than the pure-tone audiogram. The spatial release from masking task best captured variance in HHIE-S scores and remained significant after controlling for the effects of age, audibility, and cognitive score. The spatial release from masking task can complement traditional clinical measures to better account for patient's self-reported hearing difficulty. Open-source access to this test in PART supports its implementation for Spanish speakers in clinical settings around the world at low cost. https://doi.org/10.23641/asha.24470140.

Nature and characteristics of global attention to research on article processing charges

This paper examines research on article processing charges (APCs) to understand the extent of attention given by researchers and assess the status. The study analyses document types, source types, source titles, affiliations, and open access types of APC research. It also explores countries of researchers' affiliations, volume and growth of literature, and visualizes keywords based on data from Scopus. The study utilized data from the Scopus database, known as the world's largest abstract and citation database of scientific literature, to analyze article processing charges (APCs). Some analysis were carried out using inbuilt facility in Scopus while visualization and mapping were executed using Vosviewer. A total of 460 papers in 25 years, averaging 17.7 papers per year, demonstrate significant attention to this area. Many papers addressing APC were published in Green Open Access sources. Researchers from all subject categories in Scopus have contributed to APC research, but the major focus of research in the area is library and information science. Interestingly, researchers outside the field, notably from biomedicine and computer science, have also contributed significantly, reflecting interdisciplinary engagement.

Is YouTube a reliable source of information on chimeric antigen receptor T-cell therapy? An analysis.

486 Background: YouTube is an open-access source of information with more than 2.5 billion users. It plays an important role in disseminating information especially related to health, including cancer. Chimeric antigen receptor-T (CAR-T) cell therapy has significantly improved outcomes for hematologic malignancies over recent years. We aim to assess the quality and engagement parameters of the 100 most viewed videos on YouTube on CAR-T cell therapy. Methods: A systematic search was conducted on YouTube using the search terms (“CAR-T Cell therapy” AND “Cancer”). One hundred most viewed videos in English were selected. We utilized the already validated tools PEMAT and DISCERN to assess the quality of these videos on CAR-T. Additionally, we looked at the number of views, comments, and likes. Descriptive statistics and Pearson correlation tests were performed using R studio v2022.12.0-353. Results: The videos in our study had up to 3.4 million views (median number of views:19901), and the overall quality of information was fair (50%) by the DISCERN score. These videos were categorized into different sources academic (60%), media (22%), and industry (18%). The mean DISCERN score (44.27± 10.8), mean PEMAT actionability (47% ± 38%), mean PEMAT understandability (75.6% ± 15.5%). While benefits were mentioned by 67%, only 29% discussed the risks of CAR-T Cell therapy; 37% of videos promoted shared decision-making, and only 10% summarized the information at the end. There was no significant correlation between DISCERN and PEMAT scores with video engagement parameters, including likes, views, and comments. Interestingly, only 30% of videos discussed other treatment options except for CAR-T. While 88% of videos used everyday language, medical terminologies were defined by 73% of videos; 32 % of videos were broken into short sections with informative headers. Conclusions: This is the first study to our knowledge evaluating the quality of information on CAR-T therapy on YouTube. Compared to historical studies on YouTube 1, this study shows the quality of the information provided in these videos is valid and reliable. They also prove to be actionable and understandable; these videos focus on the benefits of CAR-T cell therapy and are less likely to discuss risks or shared decision-making. Contrary to previous studies2, we believe YouTube videos on CAR-T Cell therapy may serve as a supplementary source of providing information to patients wishing to learn more on this topic.

YouTube as a reliable source of information on bispecific antibodies (BsAbs): A qualitative analysis.

322 Background: YouTube is an open-access source of information. It has more than 2.5 billion users. It can play a pivotal role in educating or misinforming our cancer patients. Emerging therapeutics like BsAbs have changed the treatment paradigm for cancer over the past decade. There is scarce data to evaluate the quality of information on BsAbs uploaded on YouTube. We aim to assess the quality and engagement parameters of the most viewed videos on YouTube. Methods: A systematic search was conducted on YouTube using the search terms (“bispecific antibodies” AND “cancer”). The 70 most viewed videos were selected only in the English language. We utilized the already validated PEMAT and DISCERN tools to assess the quality of these videos on BsAbs. Additionally, we looked at the number of views, comments, and likes. Descriptive statistics and Pearson correlation tests were performed using R studio v2022.12.0-353. Results: The videos in our study had up to 50,000 views (, and the overall quality of information was poor (46.38%). These videos were categorized into different sources academic (61%), media (14.5%), and commercial (24.5%). Only 27.5% of videos discussed the benefits, 17% discussed the risks, 8.7% discussed the effect on the quality of life (QoL), and 11% discussed shared decision-making. Financial barriers were discussed only in 4% of the videos, whereas the availability of the drug was discussed in 11% of the videos. Regarding side effects, 32% of videos mention cytokine release syndrome, while 20% mention neurological toxicity. The mean DISCERN score for the videos was 41.2. A significant trend of increased DISCERN and PEMAT scores was noticed with the increasing length of the videos. Conclusions: This is the first study to evaluate the quality of information on BsAbs on YouTube. This study highlights the poor quality of information available on YouTube; these videos are less likely to discuss the risks, effects on QoL, and shared decision-making. Further efforts are needed to improve the quality and engagement of these videos based on the validated scales.[Table: see text]

Development of an Artificial Intelligence Tool for Intraoperative Guidance During Endovascular Abdominal Aortic Aneurysm Repair

Adverse events during surgery can occur in part due to errors in visual perception and judgment. Deep learning is a branch of artificial intelligence (AI) that has shown promise in providing real-time intraoperative guidance. This study aims to train and test the performance of a deep learning model that can identify inappropriate landing zones during endovascular aneurysm repair (EVAR). A deep learning model was trained to identify a "No-Go" landing zone during EVAR, defined by coverage of the lowest renal artery by the stent graft. Fluoroscopic images from elective EVAR procedures performed at a single institution and from open access sources were selected. Annotations of the "No-Go" zone were performed by trained annotators. A 10-fold cross-validation technique was used to evaluate the performance of the model against human annotations. Primary outcomes were intersection-over-union (IoU) and F1 score and secondary outcomes were pixel-wise accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). The AI model was trained using 369 images procured from 110 different patients/videos, including 18 patients/videos (44 images) from open access sources. For the primary outcomes, IoU and F1 were 0.43 (standard deviation ±0.29) and 0.53 (±0.32) respectively. For the secondary outcomes, accuracy, sensitivity, specificity, NPV, and PPV were 0.97 (±0.002), 0.51 (±0.34), 0.99 (±0.001). 0.99 (±0.002), and 0.62 (±0.34) respectively. AI can effectively identify sub-optimal areas of stent deployment during EVAR. Further directions include validating the model on datasets from other institutions and assessing its ability to predict optimal stent graft placement and clinical outcomes.