Effects of generative artificial intelligence (GenAI) patient simulation on clinical competency among global nursing undergraduates: A cross-over randomised controlled trial DOI
T. C. Fung, Siu Ling Chan,

Choi Fung Lam

et al.

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: May 2, 2025

Abstract Background and aims Clinical competency is paramount for nurses to ensure that patients receive safe, high-quality care. Generative artificial intelligence (GenAI) in nursing education gaining attention, evidence shows its suitability real-life situations. GenAI may be an effective solution enhancing nurses’ clinical competency. This study compared the impact of scenario-based patient simulation versus immersive 360° virtual reality (VR) on educational outcomes, namely competence, cultural awareness, AI readiness, effectiveness. Methods cross-over randomised controlled design was conducted from June 2024 August 2024. Forty-four undergraduate students years 1, 2, 3 were selected participate. Subgroups formed, each comprising three different years. They either a (intervention, Group B) or VR (control, A) separate days with washout period. Four self-reported questionnaires used measure competency: Competence Questionnaire (CCQ), Cultural Awareness Scale (CAS), Medical Artificial Intelligence Readiness Students (MAIRS-MS), Simulation Effectiveness Tool – Modified (SET-M). Results The revealed notable improvements competence confidence among participants. A demonstrated significant enhancements CCQ at both time points, B also showed meaningful progress. Both groups experienced changes CAS-Total scores, although these not statistically significant. In terms MAIRS-MS total score, had increase 1 (T1), improvement baseline 2 (cross-over session, T2). Regarding SET-M results, most participants (75%) felt debriefing contributed their learning, 77.3% reported increased assessment skills. Conclusions findings offer compelling effectiveness as assessed by CCQ, CAS, MAIRS-MS. Importantly, our results reveal measures, particularly within B. real-time feedback can serve powerful teaching tools improving students’ outcomes; however, exhibits notably greater effect. trial registration/number Not applicable

Language: Английский

Advances in bioinformatic methods for the acceleration of the drug discovery from nature DOI
Magdalena Maciejewska‐Turska, Milen I. Georgiev, Guoyin Kai

et al.

Phytomedicine, Journal Year: 2025, Volume and Issue: 139, P. 156518 - 156518

Published: Feb. 14, 2025

Language: Английский

Citations

1
Applications of artificial intelligence in ultrasound imaging for carpal-tunnel syndrome diagnosis: a scoping review DOI Creative Commons
Yosra Magdi Mekki, Hye Chang Rhim, Daniel H. Daneshvar

et al.

International Orthopaedics, Journal Year: 2025, Volume and Issue: unknown

Published: March 18, 2025

Abstract Purpose The purpose of this scoping review is to analyze the application artificial intelligence (AI) in ultrasound (US) imaging for diagnosing carpal tunnel syndrome (CTS), with an aim explore potential AI enhancing diagnostic accuracy, efficiency, and patient outcomes by automating tasks, providing objective measurements, facilitating earlier detection CTS. Methods We systematically searched multiple electronic databases, including Embase, PubMed, IEEE Xplore, Scopus, identify relevant studies published up January 1, 2025. Studies were included if they focused on US CTS diagnosis. Editorials, expert opinions, conference papers, dataset publications, that did not have a clear clinical algorithm excluded. Results 345 articles identified, following abstract full-text two independent reviewers, 18 manuscripts included. Of these, thirteen experimental studies, three comparative one was feasibility study. All eighteen shared common improving diagnosis and/or initial assessment using AI, aims ranging from median nerve segmentation ( n = 12) automated 9) severity classification 2). majority utilized deep learning approaches, particularly CNNs 15), some radiomics features 5) traditional machine techniques. Conclusion integration holds significant promise transforming practice. has improve streamline process, reduce variability, ultimately lead better outcomes. Further research needed address challenges related limitations, variability imaging, ethical considerations.

Language: Английский

Citations

1
Virtual cells for predictive immunotherapy DOI
Daniel Bergman, Elana J. Fertig

Nature Biotechnology, Journal Year: 2025, Volume and Issue: 43(4), P. 464 - 465

Published: April 1, 2025

Language: Английский

Citations

1
Reevaluating feature importance in gas–solid interaction predictions: A call for robust statistical methods DOI
Yoshiyasu Takefuji

Coordination Chemistry Reviews, Journal Year: 2025, Volume and Issue: 534, P. 216584 - 216584

Published: March 5, 2025

Language: Английский

Citations

1
Artificial Intelligence in Ischemic Heart Disease Prevention DOI
Shyon Parsa, Priyansh Shah,

RC Doijad

et al.

Current Cardiology Reports, Journal Year: 2025, Volume and Issue: 27(1)

Published: Feb. 1, 2025

Language: Английский

Citations

0
Comment on: “Deep convolutional neural network for automatic segmentation and classification of jaw tumors in contrast-enhanced computed tomography images” DOI
Carlos M. Ardila, Pradeep Kumar Yadalam

International Journal of Oral and Maxillofacial Surgery, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 1, 2025

Language: Английский

Citations

0
How Artificial Intelligence, Virtual Reality, and Other Digital Technologies Are Changing the Field of Pediatric Neurogastroenterology DOI
John M. Rosen

Gastroenterology Clinics of North America, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 1, 2025

Language: Английский

Citations

0
Identifying key characteristics of developed artificial intelligence algorithms to achieve meaningful impact on Canadian healthcare: a scoping review protocol DOI Creative Commons

D Coulibaly,

Azadeh Bayani, Bry Sylla

et al.

BMJ Open, Journal Year: 2025, Volume and Issue: 15(2), P. e094908 - e094908

Published: Feb. 1, 2025

Introduction Empirical data on the barriers limiting artificial intelligence (AI)’s impact healthcare are scarce, particularly within Canadian context. This study aims to address this gap by conducting a scoping review identify and evaluate AI algorithms developed researchers affiliated with institutions for patient triage, diagnosis care management. The goal is characteristics in that can be leveraged better impact. Methods analysis A will conducted following JBI Methodology Scoping Reviews reported Preferred Reporting Items Systematic Meta-Analyses extension guidelines. Relevant literature identified through comprehensive searches of MEDLINE (PubMed), CINAHL (EBSCO) Web Science (Clarivate) databases, combining keywords related AI, clinical management Studies published after 2014, English or French, discuss included. Data from selected articles extracted analysed descriptively, findings presented tabular form accompanied narrative summary. Ethics dissemination Ethical approval not required as it involves publicly available literature. expected completed November 2025. disseminated publications peer-reviewed journals presentations at conferences focused practice.

Language: Английский

Citations

0
RE: Artificial Intellegence in Medicine: Is Oral and Maxillofacial Surgery Following the Trend? DOI
Carlos M. Ardila, Pradeep Kumar Yadalam

Journal of Oral and Maxillofacial Surgery, Journal Year: 2025, Volume and Issue: 83(3), P. 269 - 269

Published: March 1, 2025

Language: Английский

Citations

0
A comprehensive review of neurotransmitter modulation via artificial intelligence: A new frontier in personalized neurobiochemistry DOI

Jaleh Bagheri Hamzyan Olia,

Arasu Raman, Chou‐Yi Hsu

et al.

Computers in Biology and Medicine, Journal Year: 2025, Volume and Issue: 189, P. 109984 - 109984

Published: March 14, 2025

Language: Английский

Citations

0