Multimodal biomedical AI
The increasing availability of biomedical data from large biobanks, electronic health records,
medical imaging, wearable and ambient biosensors, and the lower cost of genome and …
medical imaging, wearable and ambient biosensors, and the lower cost of genome and …
AI in health and medicine
Artificial intelligence (AI) is poised to broadly reshape medicine, potentially improving the
experiences of both clinicians and patients. We discuss key findings from a 2-year weekly …
experiences of both clinicians and patients. We discuss key findings from a 2-year weekly …
Towards generalist biomedical AI
Background Medicine is inherently multimodal, requiring the simultaneous interpretation
and integration of insights between many data modalities spanning text, imaging, genomics …
and integration of insights between many data modalities spanning text, imaging, genomics …
Health system-scale language models are all-purpose prediction engines
Physicians make critical time-constrained decisions every day. Clinical predictive models
can help physicians and administrators make decisions by forecasting clinical and …
can help physicians and administrators make decisions by forecasting clinical and …
[HTML][HTML] A deep learning algorithm to predict risk of pancreatic cancer from disease trajectories
Pancreatic cancer is an aggressive disease that typically presents late with poor outcomes,
indicating a pronounced need for early detection. In this study, we applied artificial …
indicating a pronounced need for early detection. In this study, we applied artificial …
Harnessing multimodal data integration to advance precision oncology
Advances in quantitative biomarker development have accelerated new forms of data-driven
insights for patients with cancer. However, most approaches are limited to a single mode of …
insights for patients with cancer. However, most approaches are limited to a single mode of …
[图书][B] Ethics and governance of artificial intelligence for health: WHO guidance: executive summary
World Health Organization - 2021 - apps.who.int
Искусственным интеллектом (ИИ) называют способность алгоритмов, закодированных
в технологии, обучаться на основе данных, чтобы они могли выполнять …
в технологии, обучаться на основе данных, чтобы они могли выполнять …
Underspecification presents challenges for credibility in modern machine learning
Machine learning (ML) systems often exhibit unexpectedly poor behavior when they are
deployed in real-world domains. We identify underspecification in ML pipelines as a key …
deployed in real-world domains. We identify underspecification in ML pipelines as a key …
Ethical machine learning in healthcare
The use of machine learning (ML) in healthcare raises numerous ethical concerns,
especially as models can amplify existing health inequities. Here, we outline ethical …
especially as models can amplify existing health inequities. Here, we outline ethical …
Improving the accuracy of medical diagnosis with causal machine learning
Abstract Machine learning promises to revolutionize clinical decision making and diagnosis.
In medical diagnosis a doctor aims to explain a patient's symptoms by determining the …
In medical diagnosis a doctor aims to explain a patient's symptoms by determining the …