This study investigates the experiences, challenges, and opportunities presented by ChatGPT AI in health sciences education, focusing on self-directed learning among students and educators at the University of Sharjah, UAE. Utilizing a descriptive qualitative research design, the study engaged participants through semi-structured interviews to explore diverse perspectives on ChatGPT's application in health sciences education. Results indicate mixed reactions: while users appreciate ChatGPT for its efficiency in academic tasks, concerns were raised about its offline functionality, linguistic inclusivity, ethical considerations, and potential impact on learning integrity and skill acquisition. Non-users expressed apprehension towards dependency on AI, diminished learning engagement, and academic dishonesty. The study concludes that while ChatGPT offers significant benefits in terms of resourcefulness and efficiency, its integration into educational settings necessitates careful consideration of accessibility, ethical standards, and the maintenance of academic integrity. These findings underline the need for a balanced approach to adopting AI technologies in education, highlighting the importance of addressing both the opportunities and challenges they present to foster an enriching learning environment.

INTRODUCTION: During COVID-19 pandemic, Telehealth was crucial to the delivery of healthcare services. it is expected that even after the pandemic is almost over, providers will probably start using telehealth on a regular basis as we transition to the “new normal.” Therefore, it is crucial to identify and resolve any discrepancies in telehealth’s effectiveness and accessibility. OBJECTIVES: Examine disparities in telehealth access and explain how frequently OB-GYN patients used telehealth during the first four months of the COVID-19 pandemic according to race/ethnicity and insurance status. METHOD: A cross-sectional design was used including a convenience sample of 9370 women who received telehealth or in-person care. RESULTS: 15,362 encounters were completed in total. 81.34% of appointments were held in person throughout the study’s time period, and 18.66% were managed by telehealth. The majority of the patients had private health insurance (n = 975, 52.4%) and were Caucasian (n = 1202, 63.4%). Compared to patients of other races, patients of Hispanic and Asian descent were less likely to attend their telehealth appointment (p< 0.001). Patients with private health insurance were more likely than those with public health insurance to show up for their telehealth appointments (p< 0.001).CONCLUSION: This study demonstrates that underserved populations, including individuals of color, those with public insurance, and others, must have greater access to and utilization of telehealth services.

Introduction: Telehealth technology and its use are not new to the field of medicine in general and OB in particular. To reduce the potential risks, make telehealth more feasible, and reduce the costs associated with its rapid adoption, it is essential to establish high-quality, evidence-based procedures for OB services. Aims: This qualitative study explored patients’ experience of receiving obstetrics and gynecological treatment via telehealth. Methods: We adopted a qualitative design. We recruited 18 women receiving care at the obstetrics and maternal and fetal medicine clinics at UMass Memorial Medical Center, Massachusetts. Semi-structured interviews were conducted and data was analyzed using qualitative thematic analysis. Results: The participants’ experience of using telehealth services emerged from the data in three themes: the experience of using modern telehealth platforms, telehealth and its perceived benefits, and telehealth and its perceived challenges. Conclusion: The overall positive experiences and consistent perceived benefits reported by most participants suggest that telehealth can be an important tool in the healthcare delivery for certain patients and situations in a post-pandemic world. This study highlighted several challenges that need to be addressed for telehealth to achieve maximum effectiveness and functionality in the future.

Background: The rapid development of technology has resulted in various advanced innovations. Many of these innovations have important applications in the healthcare industry. One of these innovations is the robotic technology that is used to assist in patient care in the intensive care unit (ICU). Objective: This study aims to describe the perspective of nurses on the use of robotic technology in patient care in the intensive care units (ICU). Method: A descriptive qualitative approach was used in this study. The research participants were 10 ICU nurses who were selected by the purposive sampling method. Data was collected through interviews following the interview guidelines. Data were analyzed using a thematic analysis approach. Results: This study found three main themes related to nurses’ perspectives on the use of robotic technology in ICU: (1) Excellent opportunity; (2) some drawbacks, and (3) feeling short of skills sometimes. Conclusion: The use of robotic technology in patient care in the ICU has both positive and negative effects. The use of robots is important to maximize the contribution of nurses in providing core nursing care to patients and families. However, this technology may dehumanize care and decrease instances f therapeutic interactions between nurses and their patients and families. Finally, to maximize benefits nurses need support and training related to the operation of robotic technology in the intensive care unit and its optimal use.

Massive amounts of data describing the genomic, transcriptomic, and epigenomic features of many different cells are produced by single-cell omics approaches. Artificial intelli- gence (AI) models are widely used to infer biological informa- tion and construct predictive models from these data due to their adaptability, scalability, and remarkable success in other disciplines. Low-dimensional representations of single-cell omics data, batch normalization, cell type classification, trajectory inference, gene regulatory network inference, and multimodal data integration have all seen a recent surge in innovation thanks to machine and deep learning. We provide a survey of recent developments in machine learning (ML) algorithms intended for analysis of single-cell omics data to aid readers in navigating this rapidly-evolving literature.

Medical technologies bolstered by AI are quickly developing into viable options for actual clinical use. Wearable, smartphones, and other mobile monitoring sensors are producing vast amounts of data that can be processed by deep learning algorithms in a variety of medical settings. Patients are eager for augmented medicine to be implemented because it will give them more control over their care and allow them to receive more tailored treatment, but doctors are hesitant to embrace the shift because they are not equipped to deal with the resulting changes in clinical practice. In addition, this phenomenon raises the questions of whether or not these cutting-edge tools should be validated by conventional clinical trials, whether or not medical schools should update their curricula to reflect the rise of digital medicine, and whether or not the ethics of constant connected monitoring should be taken into account. The purpose of this paper is to explore the current research literature and offer a holistic view of the implications of well-established clinical applications of artificial intelligence on medical professionals, hospitals, medical schools, and bioethics.

During the recent COVID-19 pandemic, healthcare services in primary healthcare centers as well as hospitals were disrupted. To cope with this condition and mitigate the effects of this pressure on the system on patients with critical chronic illnesses, the country adopted the use of telemedicine to deliver much-needed services to this in-need population of patients. Telehealth has the potential to significantly increase patient access to medical treatment in remote places and other settings with a shortage of clinicians. This report proposes the development of telehealth programs and policies in Jordan due to its potential to improve individual and community health. However, it is necessary to create and implement telehealth interventions that are tailored to the needs of individual patients and the community.

Introduction The development of internet technology and information and smartphone applications is progressing very rapidly. ON the other hand, accumulating evidence is indicating that excessive use of smartphone can cause mental and emotional health problems among adolescents. Objectives: The purpose of this study was to investigate the association between adolescent smartphone addiction and psychological and emotional health in Indonesia. Methods: This study used a cross-sectional correlational design. The study respondents were 350 adolescents aged 10-22 years and were selected through the convenience sampling method. Data were collected using the adapted and validated psychological wellbeing scale and the Smartphone addiction scale. Results: The study using Kendall's method indicated a significant correlation between the study variables (Sig. = 0.001). The correlation coefficient is -0.255, which denotes a negative, and weak to a moderate relationship. Discussion: Adolescents should exercise, attend school, and volunteer more. During unstable adolescent growth, parents must lead their children, and explain rules and conventions. Adolescents should be encouraged and directed to do more exercise, extra-school activities, and volunteer work among others. In this study it was apparent the issue of technology addiction and its possible negative effects on adolescents9emotional and mental well-being, therefore individual, group, and community interventions and assertive behavior techniques are needed to decrease adolescent smartphone addiction. Interventions such as group mentoring, counseling, and cognitive behavioral therapy could be useful in this area.