'Medical Minds and Machine Learning': Awareness and Opinions on Artificial Intelligence in Healthcare among Undergraduate Medical Students of a Tertiary Care Institute of Kolkata, India

Healthline, Год журнала: 2025, Номер unknown, С. 320 - 328

Опубликована: Янв. 10, 2025

Introduction: There is a need to incorporate Artificial Intelligence (AI) in medical education which may help expanding awareness on role of AI healthcare among the students. Objectives: To assess and opinions undergraduate students Tertiary Care Institute Kolkata identify any associated sociodemographic factors with their AI. Method: Descriptive study was conducted using consecutive sampling 288 pretested questionnaire, from August - October (2023). Participants an 'overall score AI' equal or above median were categorized as having 'high awareness'. Association profile assessed binary logistic regression. Results: Almost half (51%) belonged Phase III MBBS. Around 70.8% believed will reduce medication errors, while 83.3% opined aid healthcare-oriented research. 53.5% had low Higher odds found whose parents involved healthcare. Conclusion: high More seminars, workshops etc., be helpful generating further orientation for appropriate use applications future.

Язык: Английский

---

To Explore Nurses' Attitudes Towards Artificial Intelligence Technology: A Scoping Review

Опубликована: Янв. 1, 2025

Язык: Английский

---

Exploring artificial intelligence in orthopaedics: A collaborative survey from the ISAKOS Young Professional Task Force

Journal of Experimental Orthopaedics, Год журнала: 2025, Номер 12(1)

Опубликована: Янв. 1, 2025

Язык: Английский

---

BAKER: Bayesian Kernel Uncertainty in Domain-Specific Document Modelling

Опубликована: Фев. 26, 2025

Язык: Английский

---

A Call for Clarity: Biology Students Advocate for Guidelines for the Use of Generative AI in Higher Education

Journal of Science Education and Technology, Год журнала: 2025, Номер unknown

Опубликована: Март 13, 2025

Язык: Английский

---

Machine Learning in Medicine

IGI Global eBooks, Год журнала: 2025, Номер unknown, С. 167 - 196

Опубликована: Март 14, 2025

ML is a game-changing technology for improving diagnosis, customizing therapy, & streamlining healthcare delivery because of its capacity to handle learn from enormous volumes data. ML-based big data analysis has many benefits assimilating assessing vast intricate health care Early diagnosis monitoring drug-related safety issues were facilitated by algorithms that discovered hidden correlations between medications, medical products, adverse events. This chapter highlights the in Medicine. To achieve best possible results, it will be essential improve clinical decision support, sickness individualized treatment techniques. The discusses important keep mind when applying field, e.g., privacy, model interpretability, bias reduction, regulatory compliance. Lastly future medicine. Through responsible ethical adoption new technology, community can provide more individualized, efficient, effective patient outcomes.

Язык: Английский

---

What Ethical Issues do ChatGPT Face: A Bibliometrics Based Study

Опубликована: Март 17, 2025

ChatGPT represents a groundbreaking AI application that has garnered significant attention since its inception. However, despite promising potential, ethical implications have sparked considerable debate. This study aims to examine the key concerns surrounding governance of by conducting bibliometric analysis and cluster-based content relevant scientific literature. The identifies influential authors, countries, pivotal publications, revealing three primary categories issues associated with ChatGPT: human-related ethics, academic integrity technical literacy, artificial intelligence (AI) technology ethics derived concerns. Additionally, further refines these synthesizing frequently occurring keywords. Building on this framework, provides comprehensive discussion major challenges faced ChatGPT, as well outlining future research priorities. Furthermore, investigates knowledge base underlying ChatGPT's governance, exploring high-citation high-link-strength literature through co-citation analysis, thereby mapping landscape highlighting areas growing scholarly interest. offers valuable insights for policymakers, researchers, practitioners, emphasizing need more stringent policies, guidelines, robust design in development similar technologies.

Язык: Английский

---

Perceived artificial intelligence readiness in medical and health sciences education: a survey study of students in Saudi Arabia

BMC Medical Education, Год журнала: 2025, Номер 25(1)

Опубликована: Март 26, 2025

Abstract Background As artificial intelligence (AI) becomes increasingly integral to healthcare, preparing medical and health sciences students engage with AI technologies is critical. Objectives This study investigates the perceived readiness of in Saudi Arabia, focusing on four domains: cognition, ability, vision, ethical perspectives, using Medical Artificial Intelligences Readiness Scale for Students (MAIRS-MS). Methods A cross-sectional survey was conducted between October November 2023, targeting from various universities schools Arabia. total 1,221 e-consented participate. Data were collected via a 20-minute Google Form survey, incorporating 22-item MAIRS-MS scale. Descriptive multivariate statistical analyses performed Stata version 16.0. Cronbach alpha calculated ensure reliability, least squares linear regression used explore relationships students’ demographics their scores. Results The overall mean score 62 out 110, indicating moderate level readiness. Domain-specific scores revealed generally consistent levels readiness: cognition (58%, 23.2/40), ability (57%, 22.8/40), vision (54%, 8.1/15) ethics 8.5/15). Nearly 44.5% believed AI-related courses should be mandatory whereas only 41% reported having such required course program. Conclusions Arabia demonstrate across ethics, both solid foundation areas growth. Enhancing curricula emphasizing practical, ethical, forward-thinking skills can better equip future healthcare professionals an AI-driven future.

Язык: Английский

---

Exploring Filipino Medical Students’ Attitudes and Perceptions of Artificial Intelligence in Medical Education: A Mixed-Methods Study

MedEdPublish, Год журнала: 2025, Номер 14, С. 282 - 282

Опубликована: Апрель 1, 2025

Artificial intelligence (AI) has many implications on the practice of medicine, especially for current medical students who have to consider impact AI information available patients and ethical aspects rendering healthcare as a whole. With fast pace development in healthcare, educators struggle incorporate curriculum. The generation will likely be first use tools their practice, hence this study aims investigate perceptions role education medicine using mixed methods parallel convergent design. findings revealed that had baseline understanding its but required further training practical use. Moreover, terms future (i.e., choice specialization, doctor-patient relationship) was evident must considered by order promote responsible physicians-in-training. In conclusion, from helped identify key areas focus integration into curriculum related both clinical practice.

Язык: Английский

---

Assessing artificial intelligence knowledge among Al-Zahraa university students: A cross-sectional study

F1000Research, Год журнала: 2025, Номер 14, С. 405 - 405

Опубликована: Апрель 7, 2025

Introduction University educators’ knowledge of artificial intelligence (AI) helps them to effectively utilize these latest technological resources, significantly raising the quality teaching and learning process. Objective evaluate a sample Al-Zahraa university students' level AI knowledge. Method From 5August 2024 28November 2024, data from for Women students was obtained through an online questionnaire in cross-sectional survey study. Data downloaded Excel file Google Forms following it gathered. The questionnaire's quantitative imported analyzed. Results total number participants 498 participants; however, 89 refused answer questions, which reduced size 409. Most (90%) reported be familiar or somewhat with Artificial Intelligence. More than one half Medical School got anonymous survey. Using pre-validated, semi-structured questionnaire, 419 medical women engaged study.students (57.7%) know AI, whereas smaller percentage (42.7%) application. only quarter (25.7%) having about machine deep learning. (49%) considered as extremely important field. Conclusions study discovered that while understand well, they not much learning, applications radiology pathology.

Язык: Английский

---