Intelligent Program Research Articles

Identification of probable inhibitors for the DNA polymerase of the Monkeypox virus through the virtual screening approach

Given the paucity of antiviral treatments for monkeypox disease, caused by the Monkeypox virus (MPXV), there is a pressing need for the development/identification of new drugs to treat the infection. MPXV possesses a linear dsDNA genome that is replicated by a DNA replication complex of which DNA polymerase (DPol) forms an important component. Owing to the importance of DPol in the viral life cycle, identifying/designing small molecules abolishing its function could yield new antivirals. In this study, we first used the AlphaFold artificial intelligence program to model the 3D structure of the MPXV DPol; like the fold of DPol from other organisms, the MPXV DPol structure has the characteristic exonuclease, thumb, palm, and fingers sub-domains arrangement. Subsequently, we have identified several inhibitors through virtual screening of ZINC and antiviral libraries. Molecules with phenyl scaffold along with alanine-based and tetrazole-based molecules showed the best docking score of −8 to −10 kcal/mol. These molecules bind in the palm and fingers sub-domains interface region, which partially overlaps with the DNA binding path. The delineation of DPol/inhibitor interactions showed that majorly active site residues ASP549, ASP753, TYR550, ASN551, SER552, and ASN665 interact with the inhibitors. These compounds exhibit good Absorption, Distribution, Metabolism and Excretion properties.

A eugenic attempt to create “upper class”: Klara and the Sun by Kazuo Ishiguro

During the first third of the 20th century, scientific advances in genetic research led to an alarm for the modern world and mankind. Under the coercion of artificial intelligence and sterilization programs sponsored by the state, cultural values have been deeply influenced. British author Kazuo Ishiguro, along with his latest novel Klara and the Sun, poses several pertinent questions about the moral standards of existence and humanity. Klara and the Sun is a dystopian novel that offers a speculative future through which the effects of advanced technology, science, and artificial intelligence concepts may be decoded. Ishiguro’s serious concerns about a new society and changing social relations question human insecurity in different layers of the community. The desire to create a master race through a gene-modification process forms the main structure of the narrative. Therefore, based on eugenic attempts in the modern world, this study, addresses the violation of ethical standards that cause inequality, marginalization, and miscommunication. This study seeks to present important insights into the science of genetics and eugenics through the characters of the novel. Josie, a lifted girl, and Rick, an unlifted boy, exemplify the superiors and inferiors of the community that punctures the goals of a biocapitalist and technology-dependent society. In this sense, this article aims to uncover the results of eugenic programs that force people to modify their genes for social improvement, especially social relations.

THEORETICAL FOUNDATIONS OF URBAN TRANSPORT AND LOGISTICS SYSTEMS INTELLECTUALIZATION

Topicality. The scientific article is devoted to a research analysis of the features of intelligent technologies use for logistics processes managing, their impact on digital transformation and modernization of logistics systems. Intellectualization is a new trend in the economic development of countries derived from smart technologies, including cloud computing, mass data and the Internet. Intelligent program services based on intelligent terminals, provided by Internet enterprises, bring an unprecedented effect and challenge in this field. The relevance of the study derived from the digital transformation both the world economy and Ukraine, in particular, and within these conditions the new information technologies and intelligent systems are being formed and applied to improve and modernize transport and logistics processes. The article deals with theoretical aspects of the logistics processes intellectualization.Aim and tasks. The purpose of the work is to study the theoretical and methodological foundations for the implementation of the intellectualization concept for the management of urban transport and logistics systems in terms of adaptability.Materials and methods. The work used the methods of theoretical research, namely: the method of analysis, synthesis, the method of going from the abstract to the concrete, deduction and induction, and the method of idealization was also used in the article.Research results. During the study it was found that the features of transport and logistics systems depend on the development strategies of administrative-territorial units and the growth driver. The best countries of the world were determined by the criterion of logistics efficiency, and that made it possible to compare the results of these countries with Ukrainian indexes. Based on the results of a comparative analysis, it is substantiated that the strong position of European countries in the ranking is due to the efficient operation of their transport system and focus on the use of achievements in the field of intellectual technologies, in contrast to the weak position of Ukraine, that is due to the insufficient use of adaptive information and communication technologies in organizing of complex supply chains by subjects of transport and logistics infrastructure. The functional components and objects of intelligent transport systems are characterized. It has been established that autonomous intelligent transport systems are mainly used, which are not integrated, that, in turn, reduces their effectiveness. A theoretical and applied model for the development of urban transport and logistics systems in conditions of adaptability is built, which is based on the modern empirical and theoretical basis of the development of urban transport and logistics systems, which are influenced by the processes of globalization, socialization and intellectualization involving the use of computer, information and communication technologies when controlling vehicles and transport networks in real time. The key aspects of influence on the management of the transport system in the conditions of its socialization and intellectualization are indicated. The necessity of strategic plans and programs developing to implement the effective use of intelligent transport systems applied technologies is substantiated, that will contribute to solve the transport problems of the cities. This made it possible to determine the main conceptual foundations for the adaptation of intelligent transport technologies to the urban logistics system, which is currently in the conditions of locality, heterogeneity, with a low level of adaptability and orderliness.Conclusion. The rapid development of modern cities, the increase in the number of vehicles, the development of new routes increases the amount of information needed for analysis and promt decision-making, and this, in turn, stimulates the active use of intelligent information technologies. Currently, a new stage of logistics is developing, which manifests itself through the socialization and intellectualization of logistics activities, that involves a continuous process of knowledge obtaining, its increasing, transforming and processing to find an effective solution in the system managing at a given time. Therefore, the further development of urban transport should be based on the use of computer technology, and namely intelligent transport systems. It is expedient for cities and other territorial-administrative units to develop their own approaches corresponding to their own unique characteristics in the development of information and transport systems.

Automatic lesion detection and segmentation in 18F-flutemetamol positron emission tomography images using deep learning

BackgroundBeta amyloid in the brain, which was originally confirmed by post-mortem examinations, can now be confirmed in living patients using amyloid positron emission tomography (PET) tracers, and the accuracy of diagnosis can be improved by beta amyloid plaque confirmation in patients. Amyloid deposition in the brain is often associated with the expression of dementia. Hence, it is important to identify the anatomically and functionally meaningful areas of the human brain cortex surface using PET to diagnose the possibility of developing dementia. In this study, we demonstrated the validity of automated 18F-flutemetamol PET lesion detection and segmentation based on a complete 2D U-Net convolutional neural network via masking treatment strategies.MethodsPET data were first normalized by volume and divided into five amyloid accumulation zones through axial, coronary, and thalamic slices. A single U-Net was trained using a divided dataset for one of these zones. Ground truth segmentations were obtained by manual delineation and thresholding (1.5 × background).ResultsThe following intersection over union values were obtained for the various slices in the verification dataset: frontal lobe axial/sagittal: 0.733/0.804; posterior cingulate cortex and precuneus coronal/sagittal: 0.661/0.726; lateral temporal lobe axial/coronal: 0.864/0.892; parietal lobe axial/coronal: 0.542/0.759; and striatum axial/sagittal: 0.679/0.752. The U-Net convolutional neural network architecture allowed fully automated 2D division of the 18F-flutemetamol PET brain images of Alzheimer's patients.ConclusionsAs dementia should be tested and evaluated in various ways, there is a need for artificial intelligence programs. This study can serve as a reference for future studies using auxiliary roles and research in Alzheimer's diagnosis.

Prevent the rise of a black messiah: Madness or revolution

In the late 1960s, the Federal Bureau of Investigation (FBI), a United States of America (US) intelligence agency, developed what is famously known as Counter Intelligence Program (COINTELPRO). Its mission was to surveil, misinform, misdirect and subvert or destroy black ‘subversive’ militant groups. The main intention of COINTELPRO was to ‘prevent the rise of a messiah’ who could ‘unify, and electrify, the militant black nationalist movement’. This insight is important as it reveals how those outside of black life (FBI) would invoke biblical language to define the possibility of revolution. This article through Black liberation theology seeks to present the idea of messianism as both an experience of Africans and oppressed peoples in the Global North and Global South. The idea of messianism is part of biblical reception in Africa and the African experience of colonialism. In South Africa, messianism would be observed from the perspective of African Christianity, while another form of messianism would be seen from Nat The Prophet Turner as well as the radical identity of Christ in Black liberation theology. The article will not take lightly the idea of surveillance of black militant groups in the same way as the priestly class surveillance Christ ministry. At the same time, the article would reflect on why lunacy is associated with those that seek to subvert oppression. This article seeks to discuss the role of messianism and militancy in Black or African Christianity and highlighting biblical reception and African affectivity.Contribution: This article explores the imaginative ways the Bible or its themes have been used by both the oppressor and the oppressed, often the latter using the Bible for its prerogative, namely, revolution and liberation.

Business analytics at Florida commuter colleges: The impact and effectiveness of implementing a business analytics program

Only forty of Florida's one-hundred seventy-eight colleges and universities are public, meaning the vast majority are privately run. Many of these schools provide associate degrees or certificates (Community College Review, 2021). Commuter colleges hold the distinction of providing off-campus student living, with the majority offering two-year degrees. Despite the growing need in industry for individuals who can manage large amounts of data, commuter colleges rarely offer business analytics courses, causing many students to miss out on such employment opportunities. Most businesses struggle with analytical planning and are looking for experts who can turn data into insight (Albright & Winston, 2016). The absence of data analytics capabilities causes organizations to waste data resources at a rate of approximately sixty to seventy percent (Forrester, 2017). Intrinsically, universities of all sizes, including commuter colleges, need to train and produce more data analysts. Many major universities now offer business analytics degrees, yet business analytics degrees are available at less than twenty percent of commuter colleges. The goal of this research is to investigate whether commuter colleges would indeed benefit from business analytics programs and to determine the appropriate analytics degree curricula most optimal for these types of institutions. The paper will present an exhaustive comparison of the state of Florida's colleges and universities, including commuter colleges, examining both business intelligence and business analytics degree programs. The objective is to analyze the impact and effectiveness of these programs at larger universities and present a model for developing such programs at commuter colleges.

School Counselors’ Emotional Intelligence and Comprehensive School Counseling Program Implementation: The Mediating Role of Transformational Leadership

The authors examined whether school counselors’ emotional intelligence predicted their comprehensive school counseling program (CSCP) implementation and whether engagement in transformational leadership practices mediated the relationship between emotional intelligence and CSCP implementation. The sample for the study consisted of 792 school counselors nationwide. The findings demonstrated the significant mediating role of transformational leadership on the relationship between emotional intelligence and CSCP implementation. Implications for the counseling profession are discussed.

Effectiveness of cone-beam computed tomography-generated cephalograms using artificial intelligence cephalometric analysis

Lateral cephalograms and related analysis constitute representative methods for orthodontic treatment. However, since conventional cephalometric radiographs display a three-dimensional structure on a two-dimensional plane, inaccuracies may be produced when quantitative evaluation is required. Cone-beam computed tomography (CBCT) has minimal image distortion, and important parts can be observed without overlapping. It provides a high-resolution three-dimensional image at a relatively low dose and cost, but still shows a higher dose than a lateral cephalogram. It is especially true for children who are more susceptible to radiation doses and often have difficult diagnoses. A conventional lateral cephalometric radiograph can be obtained by reconstructing the Digital Imaging and Communications in Medicine data obtained from CBCT. This study evaluated the applicability and consistency of lateral cephalograms generated by CBCT using an artificial intelligence analysis program. Group I comprised conventional lateral cephalometric radiographs, group II comprised lateral cephalometric radiographs generated from CBCT using OnDemand 3D, and group III comprised lateral cephalometric radiographs generated from CBCT using Invivo5. All measurements in the three groups showed non-significant results. Therefore, a CBCT scan and artificial intelligence programs are efficient means when performing orthodontic analysis on pediatric or orthodontic patients for orthodontic diagnosis and planning.

Non-invasive evaluation of embryo quality for the selection of transferable embryos in human in vitro fertilization-embryo transfer.

The ultimate goal of human assisted reproductive technology is to achieve a healthy pregnancy and birth, ideally from the selection and transfer of a single competent embryo. Recently, techniques for efficiently evaluating the state and quality of preimplantation embryos using time-lapse imaging systems have been applied. Artificial intelligence programs based on deep learning technology and big data analysis of time-lapse monitoring system during in vitro culture of preimplantation embryos have also been rapidly developed. In addition, several molecular markers of the secretome have been successfully analyzed in spent embryo culture media, which could easily be obtained during in vitro embryo culture. It is also possible to analyze small amounts of cell-free nucleic acids, mitochondrial nucleic acids, miRNA, and long non-coding RNA derived from embryos using real-time polymerase chain reaction (PCR) or digital PCR, as well as next-generation sequencing. Various efforts are being made to use non-invasive evaluation of embryo quality (NiEEQ) to select the embryo with the best developmental competence. However, each NiEEQ method has some limitations that should be evaluated case by case. Therefore, an integrated analysis strategy fusing several NiEEQ methods should be urgently developed and confirmed by proper clinical trials.

Mediating effects of emotional intelligence on the relationship between empathy and humanistic care ability in nursing students: A cross-sectional descriptive study.

Patient-centered nursing holistic care is of utmost important to the nursing profession, and humanistic care cultivation has become a global nursing education concern. This study aimed to examine the relationship among emotional intelligence, empathy and humanistic care ability in nursing students, and to determine whether positive emotional intelligence could mediate the relationship between empathy and humanistic care ability. This study used a cross-sectional, descriptive design. A total of 323 nursing students was enrolled from one medical university in Heilongjiang Province, China. The emotional intelligence questionnaires, empathy scale and humanistic care ability scale were used to quantify participants' responses. There was no significant difference in gender, residence, single-child family and leader experience of nursing students' humanistic care ability. However, the significant differences were found in grade (t = 4.55, P < .01) and major interests (t = 7.06, P < .01). Obviously, there was positive correlation between positive emotional intelligence and empathy (R = 0.37, P < .01), and positive correlation between humanistic care ability and emotional intelligence (R = 0.62, P < .01), and empathy (R = 0.57, P < .01). Furthermore, emotional intelligence (β = 0.21, P < .01) had a significant mediating effect on the relationship between humanistic care ability and empathy. Nurse educators should improve the empathy of nursing students by developing and implementing emotional intelligence programs, in order to improve their humanistic care ability.

Comparison of Concordance between Chuna Manual Therapy Diagnostic Methods (Palpation, X-ray, Artificial Intelligence Program) in Lumbar Spine: An Exploratory, Cross-Sectional Clinical Study.

Before Chuna manual therapy (CMT), a manual therapy applied in Korean medicine, CMT spinal diagnosis using palpation or X-ray is performed. However, studies on the inter-rater concordance of CMT diagnostic methods, concordance among diagnostic methods, and standard CMT diagnostic methods are scarce. Moreover, no clinical studies have used artificial intelligence (AI) programs for X-ray image-based CMT diagnosis. Therefore, this study sought a feasible and standard CMT spinal diagnostic method and explored the clinical applicability of the CMT-AI program. One hundred participants were recruited, and the concordance within and among different diagnostic modalities was analyzed by dividing them into manual diagnosis (MD), X-ray image-based diagnosis (XRD) by experts and non-experts, and XRD using a CMT-AI program by non-experts. Regarding intra-group concordance, XRD by experts showed the highest concordance (used as a gold standard when comparing inter-group concordance), followed by XRD using the AI program, XRD by non-experts, and then MD. Comparing diagnostic results between the groups, concordance with the gold standard was the highest for XRD using the AI program, followed by XRD by non-experts, and MD. Therefore, XRD is a more reasonable CMT diagnostic method than MD. Furthermore, the clinical applicability of the CMT-AI program is high.

Abstract 9796: Identification of an Optimal Blood Pressure by Images of Correction of the Pathological Mechanism by Hypertension: An Angiographic, Machine Learning Analysis and Application for Personalized Medicine

Introduction: As hypertension (HTN) is a strong risk factor of coronary artery disease (CAD), what is an optimal blood pressure (BP) which could preclude CAD? Hypothesis: In industrial piping, laminar flow preserves equipment service life while turbulent flow damages the inner surface of pipes and pumps. Based on the same hydraulic principles, our hypothesis is built on the observations that turbulent flow injures the intima and triggers atherosclerosis. In order to identify an optimal BP, at which BP level, could we evidence VISUALLY the abolishment of turbulent flow at the iliac artery as proof of correction of the injuring mechanism precipitated by HTN? Methods: 210 patients with uncontrolled HTN who underwent coronary intervention and a repeat diagnostic angiogram a few months later because of unstable angina were enrolled. At the end each coronary procedure, patients underwent iliac angiogram for deployment of closure device. In a new technique of dynamic angiography, the contrast was injected until the iliac artery was completely opacified. As the injection stopped, the blood flew down and displaced the contrast. The movements of the blood in white color above a black background could be clearly identified and analyzed. At the same time, Artificial Intelligence (Machine Learning algorithms) program had 2 models built on Python. Model 1 was based on U-net and Densenet-121 for vessel segmentation. Model 2 was used for classification and movement of flow. Model 2 was trained based on the convolutional neural network. The main measurements were the type of flow (turbulent), directions (antegrade versus retrograde) and presence of collision from slamming of the retrograde against antegrade flow. Results: At baseline, 98% patients had prolonged reversed flow with turbulence. At the 2nd iliac angiogram, if the systolic BP was &lt;110mmHg, the rate of turbulence was 10%. If the systolic BP &gt;130mmHg, the turbulence was present in 70% (p&lt;0.05) Conclusions: With the uncontrolled BP imaged as collision at the iliac artery secondary to heightened distal vascular resistance, the abolishment of turbulence and return of laminar flow confirmed that the ideal systolic BP was &lt;110mmH in the application of personalized medicine. Larger studies need to confirm the above result.

Diagnosis of Interproximal Caries Lesions in Bitewing Radiographs Using a Deep Convolutional Neural Network-Based Software

The aim of this study was to evaluate the diagnostic reliability of a web-based artificial intelligence program for the detection of interproximal caries in bitewing radiographs. Three hundred bitewing radiographs of patients were subjected to the evaluation of a convolutional neural network. First, the images were visually evaluated by a previously trained and calibrated operator with radiodiagnosis experience. Then, ground truth was established and was clinically validated. For enamel caries, clinical assessment included a combination of clinical-visual and radiography evaluations. For dentin caries, clinical validation was performed by instrumentally accessing the cavity. Second, the images were uploaded and analyzed by the web-based software. Four different models were established to analyze its evaluations according to the confidence threshold (0–100%) offered by the program: model 1 (values >0% were considered positive and values of 0% were considered negative), model 2 (values ≥25% were considered positive and values <25% were considered negative), model 3 (values ≥50% were considered positive and values <50% were considered negative), and model 4 (values ≥75% were considered positive and values <75% were considered negative). The accuracy rate (A), sensitivity (S), specificity (E), positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (PLR), negative likelihood ratio (NLR), and areas under receiver operating characteristic curves (AUC) were calculated for the four models of agreement with the software. Models showed the following results respectively: A = 70.8%, 82%, 85.6%, 86.1%; S = 87%, 69.8%, 57%, 41.6%; E = 66.3%, 85.4%, 93.7%, 98.5%; PPV = 42%, 57.2%, 71.6%, 88.6%; NPV = 94.8%, 91%, 88.6%, 85.8%; PLR = 2.58, 4.78, 9.05, 27.73; NLR = 0.2, 0.35, 0.46, 0.59; AUC = 0.767, 0.777, 0.753, 0.701. Findings in the present study suggest that the artificial intelligence web-based software provides a good diagnostic reliability on the detection of dental caries. Our study highlighted model 2 for showing the best results to differentiate between healthy teeth and decayed teeth.

Improving perioperative management of surgical sets for trauma surgeries: the 4S approach

BackgroundThe perioperative management of the surgical instruments and implants that comprise sets for trauma surgeries has been identified as a complex and resource-intensive activity due to non-standardized inventories, redundant surgical instruments and unnecessary sterilization cycles. The 4S Intelligent Trauma Care program aims to improve perioperative management and thereby reduce environmental impact by utilizing standardized inventories, a sterile implant portfolio, a barcode that enables a digital safety certification, and a digitized restocking service.ObjectiveThe objective of this study was to investigate the impact of the introduction of the 4S program for the management of surgical sets in open reduction internal fixation (ORIF) trauma surgeries.MethodsThis was a single-center, quality improvement study of ORIF trauma surgeries, comparing the current practice (30 procedures) to the procedure following the introduction of the 4S program (30 procedures). The primary outcome was the proportion of procedures requiring only one sterilization cycle. Secondary outcomes were the number of sterilization cycles per procedure, set processing time across departments, total set processing costs, number of missing or damaged implants, number of cleaning cycles per procedure, time taken to assemble containers for sterilization, number of containers entering the autoclave per procedure, environmental impact, number of baskets entering the cleaning machine per procedure, and staff satisfaction.ResultsIntroduction of the 4S program resulted in a reduction in the mean number of sterilization cycles required from 2.1 to 1.0 (p < 0.001). In the current practice, only 30.0% of procedure sets were sterilized within one cycle, compared to 100.0% following introduction of the 4S program (p < 0.001). A reduction in the mean set processing time of 24.1% in the OR and 35.3% in the sterilization department was observed. Mean set processing costs for the current practice were €81.23, compared to €50.30 following introduction of the 4S program. Furthermore, following the introduction of the 4S program, procedures were associated with significant reductions in water and electricity usage, and increased staff satisfaction.ConclusionsThis quality improvement study demonstrates the substantial time and cost savings, positive environmental impact and staff satisfaction that could be achieved by streamlining surgical set management through the 4S program. To our knowledge, this is the first study of this type and our findings may be instructive to other hospitals and surgical specialties.

Design and application of an intelligent management application program for patients with an ostomy

Design and application of an intelligent management application program for patients with an ostomy

Socially facilitative robots for older adults to alleviate social isolation: A participatory design workshop approach in the US and Japan.

Social technology can improve the quality of older adults' social lives and mitigate negative mental and physical health outcomes associated with loneliness, but it should be designed collaboratively with this population. In this paper, we used participatory design (PD) methods to investigate how robots might be used as social facilitators for middle-aged and older adults (age 50+) in both the US and Japan. We conducted PD workshops in the US and Japan because both countries are concerned about the social isolation of these older adults due to their rapidly aging populations. We developed a novel approach to participatory design of future technologies that spends 2/3 of the PD session asking participants about their own life experiences as a foundation. This grounds the conversation in reality, creates rapport among the participants, and engages them in creative critical thinking. Then, we build upon this foundation, pose an abstract topic, and ask participants to brainstorm on the topic based on their previous discussion. In both countries, participants were eager to actively discuss design ideas for socially facilitative robots and imagine how they might improve their social lives. US participants suggested design ideas for telepresence robots, social distancing robots, and social skills artificial intelligence programs, while Japanese participants suggested ideas for pet robots, robots for sharing experiences, and easy-to-operate instructor robots. Comparing these two countries, we found that US participants saw robots as tools to help facilitate their social connections, while Japanese participants envisioned robots to function as surrogate companions for their parents and distract them from loneliness when they were unavailable. With this paper, we contribute to the literature in two main ways, presenting: (1) A novel approach to participatory design of future technologies that grounds participants in their everyday experience, and (2) Results of the study indicating how middle-aged and older adults from the US and Japan wanted technologies to improve their social lives. Although we conducted the workshops during the COVID-19 pandemic, many findings generalized to other situations related to social isolation, such as older adults living alone.

Design and implementation of the interdisciplinary curriculum for intelligent chemical engineering program at Taiyuan University of Technology

High quality personnel (HQP) with interdisciplinary knowledge and skills of chemical engineering, computer science, and automation are urgently needed for intelligent chemical engineering. This study explores how to make chemical engineering students proficient in applying automation and computer knowledge to solve complex problems in industrial productions. An interdisciplinary curriculum for Intelligent Chemical Engineering (ICE) program was developed by a team consisting of professors in automation, chemical engineering and computer applications at Taiyuan University of Technology’s College of Chemical Engineering. This paper present how the interdisciplinary curriculum was implemented to the volunteer groups on trial for two years and the experimental classes of ICE for three years. Project-based learning (PBL) had been proved to be an effective means to implement the curriculum within limited teaching hours. Surveys for current students and graduates showed that the students’ ability of interdisciplinary thinking and dealing with complex problems, the skills to use professional software for digital plant design and smart plant management had been greatly improved.

The Impact of Cultural Embeddedness on the Implementation of an Artificial Intelligence Program at Triage: A Qualitative Study.

Triage requires rapid determination of acuity and resources. Current modalities allow for individual judgment, with varied application of algorithmic rules. Although artificial intelligence can improve triage accuracy, gaps remain in understanding implementation facilitators and barriers, especially those related to the cultural understandings by nurses of emergency department presentations. The purpose of this study was to explore the cultural and technological elements of the implementation of an artificial intelligence clinical decision support aid (i.e., KATE) in an emergency nursing triage process in an urban community hospital on the West Coast of the United States. An exploratory qualitative study using semi-structured small group and individual interviews and constant comparison analysis strategies. The sample comprised 13 emergency department triage nurses at one site. Campinha-Bacote's theory of cultural competence framed the study. Responses yielded the overall theme of We know these people and we know these things. Supporting categories included the problem of aire; just another checkbox; gut trumps data; higher acuity with no resources; and technology as a safety net. Participants reported reliance on clinical experience and cultural knowledge to assign acuity. The implementation of an artificial intelligence program was initially received skeptically due to the acontextual nature of AI, but grew to be perceived as a safety net for triage decision making among emergency nurses.

Use of Personalized Biomarkers in Metastatic Colorectal Cancer and the Impact of AI.

Simple SummaryColorectal cancer is one of the most frequent cancers worldwide, with a high incidence and mortality. Although many treatment options are available for metastatic disease, patient survival is still limited. The molecular classification of colorectal cancer proposed in 2015 has helped us to better understand colorectal cancer and realize a more effective implementation of therapeutic sequences. It has also been observed that the existing mutational landscape is closely correlated with the epigenetics of colorectal cancer. The identification of prognostic and predictive biomarkers in this context becomes a necessity closely related to therapeutics, and artificial intelligence can be used to discover new biomarkers.Colorectal cancer is a major cause of cancer-related death worldwide and is correlated with genetic and epigenetic alterations in the colonic epithelium. Genetic changes play a major role in the pathophysiology of colorectal cancer through the development of gene mutations, but recent research has shown an important role for epigenetic alterations. In this review, we try to describe the current knowledge about epigenetic alterations, including DNA methylation and histone modifications, as well as the role of non-coding RNAs as epigenetic regulators and the prognostic and predictive biomarkers in metastatic colorectal disease that can allow increases in the effectiveness of treatments. Additionally, the intestinal microbiota’s composition can be an important biomarker for the response to strategies based on the immunotherapy of CRC. The identification of biomarkers in mCRC can be enhanced by developing artificial intelligence programs. We present the actual models that implement AI technology as a bridge connecting ncRNAs with tumors and conducted some experiments to improve the quality of the model used as well as the speed of the model that provides answers to users. In order to carry out this task, we implemented six algorithms: the naive Bayes classifier, the random forest classifier, the decision tree classifier, gradient boosted trees, logistic regression and SVM.

Gauging Stakeholder Perspectives on Artificial Intelligence in Gender-Affirming Voice Care.

As the main objective outcome measure used in gender-affirming voice care (GAVC), fundamental frequency (f0 ) often fails to accurately reflect patient perceptions of their voice. Our team developed an artificial intelligence (AI) program that provides an alternative objective outcome measure that has the potential to more accurately align with patient perceptions. To gauge stakeholder receptivity to the use of AI in GAVC before employing a novel outcome measure in transgender and nonbinary communities. This prospective qualitative study used online focus groups composed of speech-language pathologists (SLPs), transgender men (TGM), transgender women (TGW), and nonbinary (NB) individuals. Participant age, race, gender, and geographic location were recorded. Each cohort participated in a series of two focus group sessions. The first session focused on participant experiences in GAVC, whereas the second ascertained participant perspectives on the use of AI in GAVC. Transcripts of each discussion were coded using Nvivo to perform inductive thematic analysis. Seven SLPs, seven TGW, three TGM, and two NB individuals (mean [range] age, 35.5 [26-48] years) participated. Transgender and nonbinary participants were generally amenable to the technology, whereas SLPs were more hesitant about its use. Positive findings included appreciation for AI as an objective outcome measure and enthusiasm for its potential to longitudinally track progress. Hesitations concerned the actionability of using the AI and unease about the black box nature of the AI's analysis. Transgender and NB individuals were receptive to the use of AI technology in GAVC, whereas SLPs were more apprehensive about using AI. NA Laryngoscope, 133:1698-1705, 2023.