Healthcare Technology Research Articles

Leveraging Artificial Intelligence for Predictive Healthcare: A Data-Driven Approach to Early Diagnosis and Personalized Treatment

As noted, healthcare delivery systems are systems that always present organizational difficulties for any user and everyone related to these systems, but AI today is one of the widely-discussed and most frequently considered innovations that have prospects for radical improvement of the patient’s state and quality of life. AI solutions are on the verge of becoming integrated into clinical practice thanks to enhanced developments in the field, which means that there is a need to cover the part played by these technologies in healthcare and equip healthcare providers with the knowledge and resources needed to achieve that. This review article provides a broad, although dated, systematic synthesis of AI in clinical practice today, reviewing potential uses of AI in disease taxonomy and diagnosis, treatment suggestions, patient participation, and utilizing methodologies to consider the ethical and legal issues of AI and the persistent need for human insights and expertise. In order to establish the nature of the relationships and possible effects of AI in healthcare environments, the paper reviews the literature using PubMed/Medline, Scopus, and EMBASE databases. According to the findings, the application of AI technologies in health care delivery can greatly improve disease diagnosis, therapy choice, and clinical testing because, in contrast to human decision-making, AI algorithms analyze extensive data sets and outcompete human experts in specific tasks. It is accurate, cost-effective, time efficient, and free from human errors, advances the fields of pharmacogenomics and personalized medicine, optimizes the dosing of drugs, improves overall population health, establishes virtual healthcare services, and enhances mental health care, education, and trust between patients and physicians. Nevertheless, these and the following issues cannot be left unresolved: data privacy, AI bias, and the indispensability of the human factor.

Smart Machine Learning Analysis and Blockchain Healthcare Platform

The Smart Machine Learning Medical Analysis and Blockchain Healthcare Platform (SMLMAP) represents a transformative approach to medical diagnostics and data management by integrating advanced machine learning algorithms with blockchain technology. This platform is designed to accurately diagnose seven critical diseases, achieving impressive diagnostic outcomes across various conditions, including diabetes, breast cancer, heart disease, kidney disease, liver disease, malaria, and pneumonia. SMLMAP employs Random Forest algorithms for text data analysis and Convolutional Neural Networks (CNNs) for image data, ensuring rapid and precise diagnostic results. In addition to enhancing diagnostic capabilities, SMLMAP addresses significant privacy and security concerns inherent in healthcare data management. The integration of blockchain technology facilitates secure, transparent, and tamper-proof storage of patient records, empowering individuals with greater control over their medical information. This dual approach not only improves the accuracy of diagnoses but also fosters trust between patients and healthcare providers by safeguarding sensitive data against unauthorized access. Key functionalities of SMLMAP include the ability to schedule doctor appointments conveniently through the platform, ensuring that patients can receive timely medical attention. Additionally, the application provides users with a weekly healthcare magazine, delivering valuable information on health tips, disease management, and wellness advice to promote informed health decisions. By leveraging the strengths of machine learning and blockchain, SMLMAP paves the way for a more efficient, accurate, and secure healthcare ecosystem. This innovative platform not only enhances the quality of medical diagnostics but also represents a significant step forward in addressing the critical challenges of data privacy and security in the healthcare sector. The findings underscore the potential of SMLMAP to revolutionize patient care and data management in the evolving landscape of healthcare technology.

Digitalization and supply chain management: impact assessment of healthcare technology implementation on service delivery in public hospitals, Lagos, Nigeria

The study examined digitalization and supply chain management: assessing healthcare technology implementation for service delivery in Lagos General Hospital, Nigeria. It employed both qualitative and quantitative techniques. It analysed 293 questionnaires using multiple-regression, and Pearson. It used thematic to analyse data from interview and focused group discussion. The results showed a value of 3.28, with a standard deviation of 1.46, indicating the effectiveness of healthcare technology in general hospital. The H2 (R2 =.078, R = 278, F (2,290) = 12.19; p<.001) revealed digitalization-supply chain management have effect on Service-Delivery. The H3 (t = 3.71; B =.234; p<.001) revealed SCM can have an effect on achieving Sustainable-Development-Goal3. H4 (r =.070; p >.05) Revealed E-Medical Record does not have an effect on death rate in Lagos State, Nigeria. The study recommended, among other things, that all government and private healthcare facilities should harmonise EMR through SCM.

Advances in wearable biotechnology for cardiac monitoring

Wearable biotechnology is enhancing cardiac health monitoring by enabling continuous data collection for early detection and better management of cardiovascular diseases (CVDs). Recent advancements, such as multi-sensor integration, combine electrocardiography (ECG), heart rate variability, blood pressure, and oxygen saturation monitoring to provide a comprehensive cardiovascular assessment and improve diagnostic precision. Innovations in energy-harvesting technologies, like thermoelectric and piezoelectric materials, extend battery life, reducing the need for frequent recharging and increasing patient adherence. Despite these advances, challenges remain, particularly concerning data security, which requires robust encryption methods and secure data transmission protocols. Regulatory frameworks like the GDPR and HIPAA need to evolve to accommodate technological progress, ensuring new devices are safe and quickly brought to market. Enhancing interoperability with electronic health records (EHRs) is crucial to maximizing the clinical utility of wearable devices. Future research should focus on developing biochemical sensors to detect specific biomarkers in bodily fluids, refining AI algorithms for personalized diagnostics, and establishing standards for data sharing and integration. Collaboration among healthcare providers, regulatory bodies, and technology developers is essential to overcoming current barriers, expanding clinical applications, and ultimately improving patient outcomes and public health.

Advancements in Binary Solvent-Assisted Hydrogel Composites for Wearable Sensing Applications

The advancement of wearable sensing technologies has been pivotal in revolutionizing healthcare, environmental monitoring, and personal fitness. Among the diverse materials employed in these technologies, multifunctional hydrogel composites have emerged as critical components due to their unique properties, including high water content, flexibility, and biocompatibility. This review provides a comprehensive overview of the state-of-the-art in binary solvent-assisted hydrogel composites for wearable sensing applications. It begins by defining hydrogel composites and their essential attributes for wearable sensors, specifically focusing on binary solvent-assisted methods that enhance their performance and functionality. The review then delves into the applications of these composites in health monitoring, environmental detection, and sports and fitness, highlighting their role in advancing wearable technologies. Despite their promising features, there are significant challenges related to durability, sensitivity, and integration that need to be addressed to fully exploit these materials in wearable devices. This review discusses these challenges and presents potential solutions, including the development of new materials, improvement in fabrication processes, and strategies for achieving multifunctionality and sustainable design. Looking forward, the paper outlines future directions for research in this field, emphasizing the need for innovative materials and technologies that can lead to more effective, reliable, and eco-friendly wearable sensors. This review aims to inspire further research and development in the field of wearable sensing, paving the way for new applications and advancements in healthcare, environmental monitoring, and personal fitness technologies.

Influence of Blood Sampling Service Process Reengineering on Medical Services Supply: Quasi-Experimental Study.

Tertiary hospitals in China are confronted with significant challenges due to limited spatial capacity and workforce constraints, leading to saturated allocation of medical resources and restricted growth in medical service provision. The incorporation of digital health into medical service process reengineering (MSPR) marks a pivotal transformation and restructuring of conventional health service delivery models. Specifically, the application of MSPR to blood sampling services processes reengineering (BSSPR) holds promise for substantially enhancing the efficiency and quality of medical services through streamlining and optimizing these procedures. However, the comprehensive impact of BSSPR has been infrequently quantified in existing research. This study aims to investigate the influence of BSSPR on the efficiency and quality of medical services and to elucidate the key informative technological support points underpinning BSSPR. Data were collected from both the new and old laboratory information systems from August 1, 2019, to December 31, 2021. A combination of statistical description, chi-square test, and t test was used to compare check-in time and waiting time of outpatients before and after the implementation of BSSPR. An interrupted time-series design was used to analyze the impact of BSSPR on medical service efficiency and quality, enabling the control of confounding variables, including changes in medical human resources and both long- and short-term temporal trends. BSSPR had an impact on the efficiency and quality of medical services. Notably, there was a significant increase in the number of patients receiving blood sampling services, with a daily service volume increase of ~150 individuals (P=.04). The average waiting time for patients decreased substantially from 29 (SD 36) to 11 (SD 11) minutes, indicating a marked improvement in patient experience. During the peak period, the number of patients receiving blood sampling services per working hour statistically increased from 9.56 to 16.77 (P<.001). The interrupted time-series model results demonstrated a reduction in patients' waiting time by an average of 26.1 (SD 3.8; 95% CI -33.64 to -18.57) minutes. Although there was an initial decline in the number of outpatients admitted following BSSPR implementation, an upward trend was observed over time (β=1.13, 95% CI 0.91-1.36). BSSPR implementation for outpatients not only reduced waiting time and improved patients' experience but also augmented the hospital's capacity to provide medical services. This study's findings offer valuable insights into the potential advantages of BSSPR and underscore the significance of harnessing digital technologies to optimize medical service processes. This research serves as a foundational basis and provides scientific support for the promotion and application of BSSPR in other health care contexts. By continuing to explore and refine the integration of digital technologies in health care, we can further enhance patient outcomes and elevate the overall quality of medical services.

Shivering Hopes: A Qualitative Inquiry into the Experiences of Family Caregivers of Critically Ill Patients Reliant on Health Care Technology.

The aim of the study was to assess the lived experience of family caregivers of critically ill patients sustained by healthcare technologies in Benin-City, Nigeria. This study employed a hermeneutic phenomenological design. Data were collected through in-depth individual interviews with ten participants, observations, and field notes. The analysis was conducted using Paul Ricoeur's Theory of Interpretation and managed with Nvivo data management software. The study was conducted at the University of Benin Teaching Hospital (UBTH) from August 2022 to December 2023, with a sample size of 10 participants. The study's findings revealed that the majority (70%) of family caregivers were at least 30 years old, Christian, and had spent a minimum of two weeks in the intensive care unit (ICU). Ninety percent had received post-secondary education. Three themes emerged from their experiences: "Journeying into the unknown," "Technological care is an ecosystem," and "Exhibiting emotional intelligence." In addition to that, the findings also showed that upon learning of their loved one's''' transfer to the ICU, caregivers experienced mixed emotions, including palpable fear of death. This fear was linked to the high costs of management, a tense hospital environment, lack of involvement in care, institutional shortcomings, and diminished motivation due to frequent deaths in the ICU. Family caregivers must be engaged in formulating and implementing care plans to provide holistic care that meets the needs of both patients and their caregivers. Hospital administrators should take proactive steps to reduce treatment costs, making care more affordable for families. Furthermore, comprehensive programs aimed at addressing the institutional flaws identified in this study must be implemented urgently.

Selection of Biomedical Equipment for public hospitals in Sri Lanka: A stakeholder perspective

Background: Health technology is an important component in delivering healthcare services. Healthcare technology can be expensive and often does not align with the unique needs of under-resourced areas. Out of the variety of health technologies, biomedical equipment is one of the major assets for any healthcare institution, and it plays an important role in healthcare delivery.Unlike developed countries, Sri Lanka lacks a system for choosing effective biomedical equipment for hospitals. This study explored current practices to improve the biomedical equipment selection process.Purpose: The study aims to assess stakeholders’ perceptions of the decision-making process for selecting biomedical equipment in selected line ministry hospitals in the Western Province of Sri Lanka.Methodology: This cross-sectional study was conducted in four (4) line ministry hospitals, with each facility representing a specific level identified within the line ministry. A survey using a self-administered Questionnaire (SAQ) and a desk review using a checklist were conducted to assess the stakeholders' perceptions of the decision-making process in selecting biomedical equipment.Results: The stakeholders' survey revealed low awareness of the unavailability of an HTA policy, institutional guidelines, and essential biomedical equipment list. Equipment requests were mainly paper-based, finalized by a committee, and took over two days to process. Respondents found the decision-making process inconvenient and dissatisfying.The finalized requests assessed through the checklist revealed that they were incomplete, lacking crucial information, such as the Requesting Officer and infrastructure details, and not accounting for financial, environmental, and equipment demand factors.Conclusions: The decision-making system practiced was revealed to be inefficient, inconsistent, and noncomprehensive. It was also found to be made without due consideration of factors related to equipment, finance, infrastructure, human resources, and services. Therefore, establishing a proper need assessment and prioritization method with criteria is recommended.

What It Means to Be Human: A Response to Harzheim.

This response engages critically with Harzheim's review of Thomas Fuchs' In Defense of the Human Being: Foundational Questions of an Embodied Anthropology. Fuchs' work offers a profound exploration of embodied cognition, arguing that human cognition and existence are deeply shaped by our physical interactions. Harzheim's critique highlights significant aspects of Fuchs' framework, including his critique of functionalist models, the impact of transhumanist technologies, and ethical concerns in healthcare technology. This paper extends Harzheim's review by proposing an integration of functionalist and embodied cognitive models, emphasizing the need for a comprehensive evaluation of technological impacts, and advocating for a more robust ethical framework that considers social equity. Additionally, it addresses the is-ought distinction and explores the implications of technological advancements on human identity and mental health. Doede's critique is also discussed, underscoring the importance of integrating diverse cognitive models and addressing technological determinism. Overall, this response calls for a more nuanced and inclusive approach to the discourse on embodied cognition, aiming to enrich the scholarly conversation and address the complexities and implications of Fuchs' analysis.

The Influence of Health Data Spaces, Data Repositories, Data Collectives, Data Natives, and Data Commons on Artificial Intelligence for Clinical Decision-Making Among Physicians

This study investigated the perspectives of physicians regarding the influence of Health Data Spaces, Data Repositories, Data Collectives, Data Natives, and Data Commons on Clinical Decision Making in Malaysian Healthcare. In particular, this study addressed the mediating effect of artificial intelligence (AI) on the relationship between these health data concepts and Clinical Decision Making. A descriptive, analytical, cross-sectional study was conducted in public and private hospitals in Malaysia. The research population entails physicians with experience handling EMR. The sample included 160 participants. The data were collected using a researcher-made questionnaire and analyzed using the SPSS software using descriptive and Pearson Correlation tests). Health Data Spaces, Data Natives, Data Collectives, and Data Commons showed a significant fair correlation with clinical decision-making, while Data Repositories showed a moderate correlation. Additionally, when AI is introduced as a mediator, the correlation coefficients generally increase, indicating a stronger relationship between the health data variables and clinical decision-making. The study emphasizes the importance of policymakers investing in AI-driven platforms for collaboration between healthcare organizations and technology developers, offering crucial insights to empower healthcare providers in leveraging AI for improved patient care, streamlined processes, and enhanced clinical decision-making. This research holds significance in steering the advancement of health data and AI initiatives focused on enhancing patient care and outcomes. It stands out as one of the limited endeavours that investigate the impacts of novel concepts, such as Health Data Spaces and artificial intelligence, on clinical decision-making within the Malaysian healthcare system.

Acceptance of Digital Health Care Technology and the Role of Nursing Education.

As digital health care technology develops, the use of technology in the nursing field has become an essential part of nursing education. However, few studies have linked nurses' awareness of digital health care with nursing education. This study examines the direct effects and mediating effects of factors in technology acceptance on nurses' intention to accept digital health care technology. To empirically investigate these relationships, a survey was conducted among nurses in South Korea. This study emphasizes the importance of a multifaceted approach that considers personal, organizational, and innovation-related factors in understanding nurses' intentions toward acceptance of digital health care technologies. The findings confirm that performance expectancy and facilitating conditions play crucial roles in nurses' acceptance of digital health care technologies. The mediating effects of performance expectancy and facilitating conditions on intentions to accept technologies suggest that these factors can also play vital indirect roles. [J Contin Educ Nurs. 202x;5x(x):xx-xx.].

Analysis of Challenges and Opportunities for Improving the Health System in Afghanistan: Innovative Approaches and Sustainable Solutions

This research explores the challenges and opportunities for improving the health system in Afghanistan. The healthcare system is critical to any country's social and economic development. Equitable and comprehensive access to health and medical services is vital for public health and plays a critical role in improving quality of life, reducing poverty, and enhancing workforce productivity. Afghanistan, a country that has experienced decades of war, political instability, and economic crises, faces significant challenges in healthcare. The main objective is to identify the significant issues within the healthcare system and propose sustainable solutions to enhance the quality of health services. Using a mixed-method approach (qualitative and quantitative), data were collected through semi-structured interviews with experts and a review of credible scientific sources. The findings indicate that a lack of healthcare infrastructure, a shortage of specialized human resources, and management issues are among the primary challenges facing Afghanistan's healthcare system. Additionally, opportunities such as international support and utilizing modern technologies in healthcare have been identified. The study concludes that investment in infrastructure, human resource training, and strengthening international collaborations are essential to improve the healthcare situation in Afghanistan.

The Frontier Exploration and Application Prospect of Data Science

Abstract. In the era of information explosion, data floods in like a relentless tide, shaping peoples world every minute and second. Data science, the most prominent discipline of our time, wields unprecedented power to propel the development of industries across the board, serving as a bridge that connects the past with the future, granting insights into the present, and predicting trends. This article delves into the allure of data science, unveiling how it has become the key to unlocking the future world. Furthermore, this review explores in detail the core concepts, key technologies, and broad applications of data science. Through in-depth research on data acquisition, processing, analysis, and visualization, it reveals the innovative applications and significant impacts of data science in multiple fields such as business intelligence, healthcare, and financial technology. At the same time, the future trends and challenges of data science are prospectively analyzed, which provides a valuable reference for further promoting the research and practice in this field.

Factors influencing telehealth adoption among consumers in Malaysia

This study investigates the factors influencing the adoption of telehealth among consumers in Malaysia, aiming to understand the impact of effort expectancy, performance expectancy, computer self-efficacy, and trust on the intention to use telehealth, building on the Unified Theory of Acceptance and Use of Technology (UTAUT). A quantitative descriptive methodology was used, collecting data from 390 Malaysian consumers via an online survey. The data were analyzed using IBM SPSS software to evaluate the relationships between the variables. The analysis revealed significant positive relationships between all examined factors and the adoption of telehealth. Performance expectancy was the most influential factor, followed by trust, effort expectancy, and computer self-efficacy. The multiple regression model indicated that these variables collectively explain 82.1% of the variance in telehealth adoption intention. The findings provide valuable insights for providers and marketers, suggesting that telehealth platforms should focus on performance expectancy, trust, and ease of use. Additionally, the study emphasizes the need for supportive policies from the Malaysian government to enhance telehealth adoption. The results contribute to the literature on healthcare technology adoption, offering practical implications for improving telehealth implementation in Malaysia.

Digital health intervention for children with ADHD to improve mental health intervention, patient experiences, and outcomes: a study protocol

BackgroundAttention Deficit Hyperactivity Disorder (ADHD) is the most prevalent childhood psychiatric condition with profound public health, personal, and family consequences. ADHD requires comprehensive treatment; however, lack of communication and integration across multiple points of care is a substantial barrier to progress. Given the chronic and pervasive challenges associated with ADHD, innovative approaches are crucial. We developed the digital health intervention (DHI)—CoolTaCo [Cool Technology Assisting Co-regulation] to address these critical barriers. CoolTaCo uses Patient-Centered Digital Healthcare Technologies (PC-DHT) to promote co-regulation (child/parent), capture patient data, support efficient healthcare delivery, enhance patient engagement, and facilitate shared decision-making, thereby improving access to timely and targeted mental health intervention for children at significant risk for poor outcomes. The present paper will describe our planned protocol to evaluate the efficacy of CoolTaCo via randomized control trial (RCT).Methods/designWe will recruit 60 children (ages 8–12) with ADHD who will be randomized to either immediate (n = 30) or delayed (n = 30) treatment (i.e., a waitlist control group). Among those randomized to immediate treatment, half will be assigned to DHI (delivered via a smartwatch and smartphone application), the other half to an active control treatment as usual (TAU). Unlike the DHI group, the TAU group will receive the smartwatch with no assigned activities, applications, or interventions on the devices. The intervention period will last 16 weeks; after a participant has been in the delayed treatment group for 16 weeks and has completed the post-waiting period assessment, they will be randomly assigned to either the intervention or active control group. Thus, 30 participants will complete the intervention, and 30 will complete the active control, with half of the total sample completing a waitlist period.DiscussionIndividuals with ADHD have complex needs. Despite improvement in outcomes following cognitive behavioral therapies (CBT) and pharmaceutical treatment, long-term maintenance is a challenge often not addressed by traditional medical approaches, and, as we described, ineffective approaches to information sharing across points of care create further barriers to progress. Our research will fill a significant gap in translating early treatment investments and gains into long-term, sustainable outcomes.This study was registered as a clinic trial at ClinicalTrials.gov (Digital Health Intervention for Children With ADHD, ID# NCT06456372) on 06/13/2024.

The Impact and Potential of Quick Response (QR) Codes in Healthcare: A Comprehensive Review

In today’s rapidly evolving healthcare landscape, the integration of innovative technologies is becoming increasingly essential to enhance patient care, medication and overall healthcare outcomes. Quick Response (QR) codes have emerged as a versatile tool with significant potential to revolutionize such aspects of the healthcare industry. Through a review of 30 studies, we uncover the significant impact of integrating QR codes into healthcare systems. Across various domains, QR codes prove instrumental in enhancing patient care, streamlining workflows, and improving communication between healthcare professionals and patients. Notable findings include the role of QR in ensuring medication safety and advancing education as well as training within healthcare settings. Despite some challenges, user satisfaction remains high, underscoring QR codes’ effectiveness in optimizing healthcare delivery and outcomes from a human-centred perspective. This includes considering usability, cognitive load, and ergonomic design, all of which are crucial for maximizing the benefits of QR code technology in healthcare.

Diabetes Control and Clinical Outcomes among Children Attending a Regional Paediatric Diabetes Service in Australia.

Australian children with diabetes commonly struggle to achieve optimal glycaemic control, with minimal improvement observed over the past decade. The scarcity of research in the rural and regional Australian context is concerning, given high incidence rates and prominent barriers to healthcare access in these areas. We conducted a retrospective audit of 60 children attending a regional Australian paediatric diabetes service between January 2020 and December 2023. The majority of patients had type 1 diabetes (n = 57, 95.0%); approximately equal numbers were managed with continuous subcutaneous insulin infusion (CSII) pumps vs. multiple daily injections (MDIs), whilst 88.3% (n = 53) also utilised continuous glucose monitoring (CGM). The mean age at last visit was 14.0 years (SD, 3.4), mean diabetes duration 5.8 years (SD, 4.6), and mean HbA1c level 8.1% (65.3 mmol/mol); only 36.8% achieved the national target of 7.5% (58 mmol/mol). Mean BMI-SDS was 0.8 (SD, 1.0); almost half (n = 27, 45.0%) were overweight or obese. Many patients had mental health conditions (31.7%), which were associated with higher hospitalisation rates (p = 0.007). The attendance rate was 83.2%, with a mean of 3.3 clinic visits per year (SD, 0.7); higher attendance rates were associated with increased CGM sensor usage (r = 0.395, p = 0.007 Overall, the diabetes service performed similarly to other clinics with regards to glycaemic control. Whilst achieving treatment targets and addressing comorbidities remains a challenge, the decent attendance and the high uptake of healthcare technologies is commendable. Further efforts are needed to improve diabetes management for this regional community.

Analysis of Challenges and Opportunities for Improving the Health System in Afghanistan: Innovative Approaches and Sustainable Solutions

This research explores the challenges and opportunities for improving the health system in Afghanistan. The main objective is to identify the major issues within the healthcare system and propose sustainable solutions to enhance the quality of health services. Using a mixed-method approach (qualitative and quantitative), data were collected through semi-structured interviews with experts and a review of credible scientific sources. The findings indicate that a lack of healthcare infrastructure, a shortage of specialized human resources, and management issues are among the primary challenges facing Afghanistan's healthcare system. Additionally, opportunities such as international support and utilizing modern technologies in healthcare have been identified. The study concludes that investment in infrastructure, human resource training, and strengthening international collaborations are essential to improve the healthcare situation in Afghanistan. The study's recommendations emphasize the importance of investments in infrastructure, comprehensive training for health workers, and international partnerships to strengthen service delivery. This analysis provides practical insights for policymakers and international organizations, which could ultimately help build a more resilient health framework in Afghanistan.

Medical students and house officers’ perception, attitude and potential barriers towards artificial intelligence in Egypt, cross sectional survey

BackgroundArtificial intelligence (AI) is one of the sectors of medical research that is expanding the fastest right now in healthcare. AI has rapidly advanced in the field of medicine, helping to treat a variety of illnesses and reducing the number of diagnostic and follow-up errors.ObjectiveThis study aims to assess the perception and attitude towards artificial intelligence (AI) among medical students & house officers in Egypt.MethodsAn online cross-sectional study was done using a questionnaire on the Google Form website. The survey collected demographic data and explored participants’ perception, attitude & potential barriers towards AI.ResultsThere are 1,346 responses from Egyptian medical students (25.8%) & house officers (74.2%). Most participants have inadequate perception (76.4%) about the importance and usage of AI in the medical field, while the majority (87.4%) have a negative attitude. Multivariate analysis revealed that age is the only independent predictor of AI perception (AOR = 1.07, 95% CI 1.01–1.13). However, perception level and gender are both independent predictors of attitude towards AI (AOR = 1.93, 95% CI 1.37–2.74 & AOR = 1.80, 95% CI 1.30–2.49, respectively).ConclusionThe study found that medical students and house officers in Egypt have an overall negative attitude towards the integration of AI technologies in healthcare. Despite the potential benefits of AI-driven digital medicine, most respondents expressed concerns about the practical application of these technologies in the clinical setting. The current study highlights the need to address the concerns of medical students and house officers towards AI integration in Egypt. A multi-pronged approach, including education, targeted training, and addressing specific concerns, is necessary to facilitate the wider adoption of AI-enabled healthcare.

Can AI hear me? Nine facts about the artificial intelligence scribe

This article summarizes important features of artificial intelligence scribe (AIS) and its application as a digital scribe through the utilization of voice recognition as it is integrated into the clinical practice of medicine. This discussion will include 1) digital scribe technology, 2) practical utility, 3) liability, 4) privacy, 5) integration to electronic health records (EHR), 6) technology burden, 7) case use, 8) AIS documentation styles, and 9) cost. The use of AIS technology in healthcare is a promising tool and will result in variability applications requiring healthcare providers to be aware of the complexities of the tool before utilization, during implementation, the effect of it on workflow, and its acceptance by the patients we serve. AIS technology promises to decrease the cognitive workload of the healthcare provider, through application by relieving the ever-increasing burden of documenting the medical record, organizing, and capturing relevant medical data, by improving integration of this data into cumbersome EHRs, thus providing better work life balance. The authors piloted a version of an AIS in a primarily Spanish patient population. This article provides a unique perspective towards the usability of an AIS in a Hispanic patient population.