Developmental Medicine & Child Neurology, Год журнала: 2025, Номер unknown
Опубликована: Фев. 22, 2025
Язык: Английский
Nature Medicine, Год журнала: 2025, Номер unknown
Опубликована: Янв. 8, 2025
Язык: Английский
Процитировано
13
Nature Medicine, Год журнала: 2025, Номер unknown
Опубликована: Фев. 5, 2025
Язык: Английский
Процитировано
6
European Journal of Human Genetics, Год журнала: 2025, Номер unknown
Опубликована: Янв. 13, 2025
Abstract Artificial intelligence (AI) has been growing more powerful and accessible, will increasingly impact many areas, including virtually all aspects of medicine biomedical research. This review focuses on previous, current, especially emerging applications AI in clinical genetics. Topics covered include a brief explanation different general categories AI, machine learning, deep generative AI. After introductory explanations examples, the discusses genetics three main categories: diagnostics; management therapeutics; support. The concludes with short, medium, long-term predictions about ways that may affect field Overall, while precise speed at which continue to change is unclear, as are overall ramifications for patients, families, clinicians, researchers, others, it likely result dramatic evolution It be important those involved prepare accordingly order minimize risks maximize benefits related use field.
Язык: Английский
Процитировано
3
The Lancet Digital Health, Год журнала: 2025, Номер 7(2), С. e108 - e109
Опубликована: Янв. 29, 2025
Язык: Английский
Процитировано
2
The Innovation Medicine, Год журнала: 2025, Номер unknown, С. 100120 - 100120
Опубликована: Янв. 1, 2025
<p>Artificial intelligence (AI) is driving transformative changes in the field of medicine, with its successful application relying on accurate data and rigorous quality standards. By integrating clinical information, pathology, medical imaging, physiological signals, omics data, AI significantly enhances precision research into disease mechanisms patient prognoses. technologies also demonstrate exceptional potential drug development, surgical automation, brain-computer interface (BCI) research. Through simulation biological systems prediction intervention outcomes, enables researchers to rapidly translate innovations practical applications. While challenges such as computational demands, software ethical considerations persist, future remains highly promising. plays a pivotal role addressing societal issues like low birth rates aging populations. can contribute mitigating rate through enhanced ovarian reserve evaluation, menopause forecasting, optimization Assisted Reproductive Technologies (ART), sperm analysis selection, endometrial receptivity fertility remote consultations. In posed by an population, facilitate development dementia models, cognitive health monitoring strategies, early screening systems, AI-driven telemedicine platforms, intelligent smart companion robots, environments for aging-in-place. profoundly shapes medicine.</p>
Язык: Английский
Процитировано
2
Annals of Biomedical Engineering, Год журнала: 2025, Номер unknown
Опубликована: Янв. 6, 2025
Язык: Английский
Процитировано
1
RMD Open, Год журнала: 2025, Номер 11(1), С. e004309 - e004309
Опубликована: Янв. 1, 2025
Artificial intelligence (AI) is transforming rheumatology research, with a myriad of studies aiming to improve diagnosis, prognosis and treatment prediction, while also showing potential capability optimise the research workflow, drug discovery clinical trials. Machine learning, key element discriminative AI, has demonstrated ability accurately classifying rheumatic diseases predicting therapeutic outcomes by using diverse data types, including structured databases, imaging text. In parallel, generative driven large language models, becoming powerful tool for optimising workflow supporting content generation, literature review automation decision support. This explores current applications future both AI in rheumatology. It highlights challenges posed these technologies, such as ethical concerns need rigorous validation regulatory oversight. The integration promises substantial advancements but requires balanced approach benefits minimise possible downsides.
Язык: Английский
Процитировано
1
npj Digital Medicine, Год журнала: 2025, Номер 8(1)
Опубликована: Фев. 5, 2025
Abstract Faced with challenging cases, doctors are increasingly seeking diagnostic advice from large language models (LLMs). This study aims to compare the ability of LLMs and human physicians diagnose cases. An offline dataset 67 cases primary gastrointestinal symptoms was used solicit possible diagnoses seven 22 gastroenterologists. The by Claude 3.5 Sonnet covered highest proportion (95% confidence interval [CI]) instructive (76.1%, [70.6%–80.9%]), significantly surpassing all gastroenterologists ( p < 0.05 for all). achieved a higher coverage rate CI) than that using search engines or other traditional resource (76.1% [70.6%–80.9%] vs. 45.5% [40.7%-50.4%], 0.001). highlights advanced may assist instructive, time-saving, cost-effective scopes in
Язык: Английский
Процитировано
1
JAMA Health Forum, Год журнала: 2025, Номер 6(2), С. e250289 - e250289
Опубликована: Фев. 6, 2025
This JAMA Forum discusses the ways in which recent changes to US Food and Drug Administration (FDA) policies related regulation of artificial intelligence (AI) have added new uncertainties for use AI tools medicine.
Язык: Английский
Процитировано
1
Korean Journal of Radiology, Год журнала: 2025, Номер 26
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
1