Generative AI in Medical Imaging: Applications, Challenges, and Ethics DOI
Mohamad Koohi‐Moghadam,

Kyongtae Ty Bae

Journal of Medical Systems, Journal Year: 2023, Volume and Issue: 47(1)

Published: Aug. 31, 2023

Language: Английский

Foundation models for generalist medical artificial intelligence DOI Creative Commons
Michael Moor,

Oishi Banerjee,

Zahra Shakeri Hossein Abad

et al.

Nature, Journal Year: 2023, Volume and Issue: 616(7956), P. 259 - 265

Published: April 12, 2023

The exceptionally rapid development of highly flexible, reusable artificial intelligence (AI) models is likely to usher in newfound capabilities medicine. We propose a new paradigm for medical AI, which we refer as generalist AI (GMAI). GMAI will be capable carrying out diverse set tasks using very little or no task-specific labelled data. Built through self-supervision on large, datasets, flexibly interpret different combinations modalities, including data from imaging, electronic health records, laboratory results, genomics, graphs text. Models turn produce expressive outputs such free-text explanations, spoken recommendations image annotations that demonstrate advanced reasoning abilities. Here identify high-impact potential applications and lay specific technical training datasets necessary enable them. expect GMAI-enabled challenge current strategies regulating validating devices medicine shift practices associated with the collection large datasets.

Language: Английский

Citations

739
Scientific discovery in the age of artificial intelligence DOI
Hanchen Wang, Tianfan Fu, Yuanqi Du

et al.

Nature, Journal Year: 2023, Volume and Issue: 620(7972), P. 47 - 60

Published: Aug. 2, 2023

Language: Английский

Citations

708
The next generation of evidence-based medicine DOI Open Access
Vivek Subbiah

Nature Medicine, Journal Year: 2023, Volume and Issue: 29(1), P. 49 - 58

Published: Jan. 1, 2023

Language: Английский

Citations

337
Attention is not all you need: the complicated case of ethically using large language models in healthcare and medicine DOI Creative Commons
Stefan Harrer

EBioMedicine, Journal Year: 2023, Volume and Issue: 90, P. 104512 - 104512

Published: March 15, 2023

Language: Английский

Citations

285
The shaky foundations of large language models and foundation models for electronic health records DOI Creative Commons
Michael Wornow, Yizhe Xu, Rahul Thapa

et al.

npj Digital Medicine, Journal Year: 2023, Volume and Issue: 6(1)

Published: July 29, 2023

The success of foundation models such as ChatGPT and AlphaFold has spurred significant interest in building similar for electronic medical records (EMRs) to improve patient care hospital operations. However, recent hype obscured critical gaps our understanding these models' capabilities. In this narrative review, we examine 84 trained on non-imaging EMR data (i.e., clinical text and/or structured data) create a taxonomy delineating their architectures, training data, potential use cases. We find that most are small, narrowly-scoped datasets (e.g., MIMIC-III) or broad, public biomedical corpora PubMed) evaluated tasks do not provide meaningful insights usefulness health systems. Considering findings, propose an improved evaluation framework measuring the benefits is more closely grounded metrics matter healthcare.

Language: Английский

Citations

147
Thermal immuno-nanomedicine in cancer DOI
Zhe Yang, Di Gao, Jing Zhao

et al.

Nature Reviews Clinical Oncology, Journal Year: 2023, Volume and Issue: 20(2), P. 116 - 134

Published: Jan. 5, 2023

Language: Английский

Citations

142
Multimodal data fusion for cancer biomarker discovery with deep learning DOI
Sandra Steyaert,

Marija Pizurica,

Divya Nagaraj

et al.

Nature Machine Intelligence, Journal Year: 2023, Volume and Issue: 5(4), P. 351 - 362

Published: April 6, 2023

Language: Английский

Citations

128
A physicochemical-sensing electronic skin for stress response monitoring DOI
Changhao Xu, Yu Song, Juliane R. Sempionatto

et al.

Nature Electronics, Journal Year: 2024, Volume and Issue: 7(2), P. 168 - 179

Published: Jan. 19, 2024

Language: Английский

Citations

128
Artificial intelligence in healthcare: Complementing, not replacing, doctors and healthcare providers DOI Creative Commons
Emre Sezgın

Digital Health, Journal Year: 2023, Volume and Issue: 9

Published: Jan. 1, 2023

The utilization of artificial intelligence (AI) in clinical practice has increased and is evidently contributing to improved diagnostic accuracy, optimized treatment planning, patient outcomes. rapid evolution AI, especially generative AI large language models (LLMs), have reignited the discussions about their potential impact on healthcare industry, particularly regarding role providers. Concerning questions, “can replace doctors?” “will doctors who are using those not it?” been echoed. To shed light this debate, article focuses emphasizing augmentative healthcare, underlining that aimed complement, rather than replace, fundamental solution emerges with human–AI collaboration, which combines cognitive strengths providers analytical capabilities AI. A human-in-the-loop (HITL) approach ensures systems guided, communicated, supervised by human expertise, thereby maintaining safety quality services. Finally, adoption can be forged further organizational process informed HITL improve multidisciplinary teams loop. create a paradigm shift complementing enhancing skills providers, ultimately leading service quality, outcomes, more efficient system.

Language: Английский

Citations

116
Artificial intelligence for predictive biomarker discovery in immuno-oncology: a systematic review DOI
Arsela Prelaj, Vanja Mišković,

Michele Zanitti

et al.

Annals of Oncology, Journal Year: 2023, Volume and Issue: 35(1), P. 29 - 65

Published: Oct. 23, 2023

Language: Английский

Citations

99