Ars Pharmaceutica (Internet), Год журнала: 2025, Номер 66(2), С. 122 - 125
Опубликована: Март 19, 2025
BMC Medical Ethics, Год журнала: 2024, Номер 25(1)
Опубликована: Май 16, 2024
Abstract Background Integrating artificial intelligence (AI) into healthcare has raised significant ethical concerns. In pharmacy practice, AI offers promising advances but also poses challenges. Methods A cross-sectional study was conducted in countries from the Middle East and North Africa (MENA) region on 501 professionals. 12-item online questionnaire assessed concerns related to adoption of practice. Demographic factors associated with were analyzed via SPSS v.27 software using appropriate statistical tests. Results Participants expressed about patient data privacy (58.9%), cybersecurity threats potential job displacement (62.9%), lack legal regulation (67.0%). Tech-savviness basic understanding correlated higher concern scores ( p < 0.001). Ethical implications include need for informed consent, beneficence, justice, transparency use AI. Conclusion The findings emphasize importance guidelines, education, autonomy adopting Collaboration, privacy, equitable access are crucial responsible
Язык: Английский
Процитировано
21
Journal of Personalized Medicine, Год журнала: 2024, Номер 14(1), С. 107 - 107
Опубликована: Янв. 18, 2024
Accurate information regarding oxalate levels in foods is essential for managing patients with hyperoxaluria, nephropathy, or those susceptible to calcium stones. This study aimed assess the reliability of chatbots categorizing based on their content. We assessed accuracy ChatGPT-3.5, ChatGPT-4, Bard AI, and Bing Chat classify dietary content per serving into low (<5 mg), moderate (5–8 high (>8 mg) categories. A total 539 food items were processed through each chatbot. The was compared between stratified by AI had highest 84%, followed (60%), GPT-4 (52%), GPT-3.5 (49%) (p < 0.001). There a significant pairwise difference chatbots, except = 0.30). all decreased higher degree categories but remained having accuracy, regardless considerable variation classifying consistently showed Chat, GPT-4, GPT-3.5. These results underline potential management at-risk patient groups need enhancements chatbot algorithms clinical accuracy.
Язык: Английский
Процитировано
19
Journal of the American Medical Informatics Association, Год журнала: 2024, Номер 31(6), С. 1411 - 1422
Опубликована: Апрель 19, 2024
Current Clinical Decision Support Systems (CDSSs) generate medication alerts that are of limited clinical value, causing alert fatigue. Artificial Intelligence (AI)-based methods may help in optimizing alerts. Therefore, we conducted a scoping review on the current state use AI to optimize hospital setting. Specifically, aimed identify applied used together with their performance measures and main outcome measures.
Язык: Английский
Процитировано
17
Exploratory Research in Clinical and Social Pharmacy, Год журнала: 2024, Номер 15, С. 100481 - 100481
Опубликована: Июль 18, 2024
Generative artificial intelligence (Gen-AI), exemplified by the widely adopted ChatGPT, has garnered significant attention in recent years. Its application spans various health education domains, including pharmacy, where its potential benefits and drawbacks have become increasingly apparent. Despite growing adoption of Gen-AIsuch as ChatGPT pharmacy education, there remains a critical need to assess mitigate associated risks. This review exploresthe literature strategies for mitigating risks with integration Gen-AI education.
Язык: Английский
Процитировано
15
Deleted Journal, Год журнала: 2024, Номер 2024, С. 14 - 19
Опубликована: Фев. 15, 2024
The objective of this systematic review was to assess the adequacy current medication management in Ghana considering risks posed by increased artificial intelligence (AI) automation pharmacies worldwide A qualitative comparative approach used despite reviewed 1994 Pharmacy Act against recognition AI challenges and international governance guidelines . results revealed flaws terms quality prerequisites, transparency checklists liability mechanisms developed for systems compared existing regulations manual process. Outdated approaches patient care that fail ensure safety or address threats accuracy recommendations from data collection biases technical errors. Proposed changes include a requirement usability testing before approving pharmacy deployments creation board post-implementation validity. Updating deal with modern equipment puts innovation responsible regulation fast-paced healthcare industry. This study contributes significantly preliminary research on policy readiness Ghanaian legal context, suggests feasible methodology exploring differences use companies countries competing technology disturbing, increasingly beyond date code. Early government reform helps keep pace realities adoption.
Язык: Английский
Процитировано
11
BMJ Open, Год журнала: 2025, Номер 15(3), С. e098290 - e098290
Опубликована: Март 1, 2025
Introduction Methods to adopt artificial intelligence (AI) in healthcare clinical practice remain unclear. The potential for rapid integration of AI-enabled technologies across settings coupled with the growing digital divide health sector highlights need examine AI use by professionals, especially allied disciplines emerging such as physiotherapy, occupational therapy, speech pathology, podiatry and dietetics. This protocol details methodology a scoping review on technology sectors workforce. research question is ‘How used workforce improve patient safety, quality care outcomes, what evidence supporting this use?’ analysis will follow Joanna Briggs Institute guidelines. Databases be searched from 17 24 March 2025 include PubMed/Medline, Embase, PsycINFO Cummulative Index Nursing Allied Health Literature databases. Dual screening against inclusion criteria applied study selection. Peer-reviewed articles reporting primary published English within last 10 years included. Studies evaluated using Quality Assessment Diverse tool. map existing literature identify key themes related Ethics dissemination No ethics approval sought, only secondary outputs used. Findings disseminated through peer-reviewed publication presentations at workshops conferences. Trial registration number Open Science Framework Protocol Registration https://osf.io/r7t4s
Язык: Английский
Процитировано
2
JACCP JOURNAL OF THE AMERICAN COLLEGE OF CLINICAL PHARMACY, Год журнала: 2025, Номер unknown
Опубликована: Фев. 13, 2025
Abstract Almost every facet of modern biomedical research involves artificial intelligence (AI). This ACCP commentary forecasts the role AI in clinical pharmacy and scholarship. The potential benefits/opportunities together with limitations/challenges are reviewed for stages scientific method including (1) developing question(s), study design, execution; (2) data analysis; (3) reporting dissemination research. Benefits opportunities include streamlining hypothesis generation facilitating overcoming limitations traditional statistical analysis techniques, manuscript development dissemination, expediting peer review. Limitations challenges introduction biases subject recruitment; false information, also known as “AI hallucinations”; concern “black box” analyses that difficult to validate; legal liabilities; lack accountability; need investigators ensure accuracy integrity AI‐generated content. In summary, rapid progress capabilities has great revolutionize accelerate scholarship; however, it is imperative recognize mitigate introduced by AI.
Язык: Английский
Процитировано
1
Healthcare, Год журнала: 2024, Номер 12(7), С. 788 - 788
Опубликована: Апрель 5, 2024
Prescribing medications is a fundamental practice in the management of illnesses that necessitates in-depth knowledge clinical pharmacology. Polypharmacy, or concurrent use multiple by individuals with complex health conditions, poses significant challenges, including an increased risk drug interactions and adverse reactions. The Saudi Vision 2030 prioritises enhancing healthcare quality safety, addressing polypharmacy. Artificial intelligence (AI) offers promising tools to optimise medication plans, predict reactions ensure safety. This review explores AI’s potential revolutionise polypharmacy Arabia, highlighting practical applications, challenges path forward for integration AI solutions into practices.
Язык: Английский
Процитировано
8
Advances in educational marketing, administration, and leadership book series, Год журнала: 2024, Номер unknown, С. 275 - 320
Опубликована: Окт. 10, 2024
Artificial intelligence (AI) has become a disruptive force that is changing conventional wisdom in wide range of sectors. This thorough analysis threads through the complex web AI applications, providing nuanced examination its effects several industries while narrowing down on revolutionary impact education. Education stands as cornerstone experiencing significant changes, radically how students learn and educators educate, companies throughout world adjust to AI. The assessment begins by outlining broad important industries. healthcare redefining diagnostic accuracy treatment techniques, with consequences for professional Gamification, adaptive learning platforms, intelligent tutoring systems are essential instruments face study examines advantages these including improved accessibility, reduced administrative procedures, personalized experiences.
Язык: Английский
Процитировано
7
Information, Год журнала: 2025, Номер 16(2), С. 131 - 131
Опубликована: Фев. 11, 2025
Integrating artificial intelligence (AI) into pharmacy operations and drug discovery represents a groundbreaking milestone in healthcare, offering unparalleled opportunities to revolutionize medication management, accelerate development, deliver truly personalized patient care. This review examines the pivotal impact of AI critical domains, including repurposing, clinical trials, pharmaceutical productivity enhancement. By significantly reducing human workload, improving precision, shortening timelines, empowers industry achieve ambitious objectives efficiently. study delves tools methodologies enabling implementation, addressing ongoing challenges such as data privacy, algorithmic transparency, ethical considerations while proposing actionable strategies overcome these barriers. Furthermore, it offers insights future pharmacy, highlighting its potential foster innovation, enhance efficiency, improve outcomes. research is grounded rigorous methodology, employing advanced collection techniques. A comprehensive literature was conducted using platforms PubMed, Semantic Scholar, multidisciplinary databases, with AI-driven algorithms refining retrieval relevant up-to-date studies. Systematic scoping incorporated diverse perspectives from medical, pharmaceutical, computer science leveraging natural language processing for trend analysis thematic content coding identify patterns, challenges, emerging applications. Modern visualization synthesized findings explicit graphical representations, view key role shaping healthcare.
Язык: Английский
Процитировано
1