Generative AI in Medicine — Evaluating Progress and Challenges

New England Journal of Medicine, Journal Year: 2025, Volume and Issue: unknown

Published: April 10, 2025

Language: Английский

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Applying artificial intelligence to rare diseases: a literature review highlighting lessons from Fabry disease

Orphanet Journal of Rare Diseases, Journal Year: 2025, Volume and Issue: 20(1)

Published: April 17, 2025

Abstract Background Use of artificial intelligence (AI) in rare diseases has grown rapidly recent years. In this review we have outlined the most common machine-learning and deep-learning methods currently being used to classify analyse large amounts data, such as standardized images or specific text electronic health records. To illustrate how these been adapted developed for use with diseases, focused on Fabry disease, an X-linked genetic disorder caused by lysosomal α-galactosidase. A deficiency that can result multiple organ damage. Methods We searched PubMed articles focusing AI, disease published anytime up 08 January 2025. Further searches, limited between 01 2021 31 December 2023, were also performed using double combinations keywords related AI each affected diseases. Results total, 20 included. field, may be applied prospectively populations identify patients, retrospectively data sets diagnose a previously overlooked disease. Different facilitate diagnosis, help monitor progression organs, potentially contribute personalized therapy development. The implementation general healthcare medical imaging centres raise awareness prompt practitioners consider conditions earlier diagnostic pathway, while chatbots telemedicine accelerate patient referral experts. technologies generate ethical risks, prompting new regulatory frameworks aimed at addressing issues established Europe United States. Conclusion AI-based will lead substantial improvements diagnosis management need human guarantee is key issue pursuing innovation ensuring involvement remains centre care during technological revolution.

Language: Английский

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Artificial intelligence in preclinical research: enhancing digital twins and organ-on-chip to reduce animal testing

Drug Discovery Today, Journal Year: 2025, Volume and Issue: unknown, P. 104360 - 104360

Published: April 1, 2025

Artificial intelligence (AI) is reshaping preclinical drug research offering innovative alternatives to traditional animal testing. Advanced techniques, including machine learning (ML), deep (DL), AI-powered digital twins (DTs), and AI-enhanced organ-on-a-chip (OoC) platforms, enable precise simulations of complex biological systems. AI plays a critical role in overcoming the limitations DTs OoC, improving their predictive power scalability. These technologies facilitate early-stage, reliable evaluations safety efficacy, addressing ethical concerns, reducing costs, accelerating development while adhering 3Rs principle (Replace, Reduce, Refine). By integrating with these advanced models, can achieve greater accuracy efficiency discovery. This review examines transformative impact research, highlighting its advancements, challenges, steps needed establish as cornerstone efficient

Language: Английский

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Enhancing organoid technology with carbon-based nanomaterial biosensors: Advancements, challenges, and future directions

Advanced Drug Delivery Reviews, Journal Year: 2025, Volume and Issue: unknown, P. 115592 - 115592

Published: May 1, 2025

Language: Английский

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