Shifting machine learning for healthcare from development to deployment and from models to data
In the past decade, the application of machine learning (ML) to healthcare has helped drive
the automation of physician tasks as well as enhancements in clinical capabilities and …
the automation of physician tasks as well as enhancements in clinical capabilities and …
The future of early cancer detection
A proactive approach to detecting cancer at an early stage can make treatments more
effective, with fewer side effects and improved long-term survival. However, as detection …
effective, with fewer side effects and improved long-term survival. However, as detection …
A programmable diffractive deep neural network based on a digital-coding metasurface array
The development of artificial intelligence is typically focused on computer algorithms and
integrated circuits. Recently, all-optical diffractive deep neural networks have been created …
integrated circuits. Recently, all-optical diffractive deep neural networks have been created …
Swarm learning for decentralized and confidential clinical machine learning
S Warnat-Herresthal, H Schultze, KL Shastry… - Nature, 2021 - nature.com
Fast and reliable detection of patients with severe and heterogeneous illnesses is a major
goal of precision medicine,. Patients with leukaemia can be identified using machine …
goal of precision medicine,. Patients with leukaemia can be identified using machine …
Where medical statistics meets artificial intelligence
Where Medical Statistics Meets Artificial Intelligence | New England Journal of Medicine Skip to
main content The New England Journal of Medicine homepage Advanced Search SEARCH …
main content The New England Journal of Medicine homepage Advanced Search SEARCH …
Privacy and artificial intelligence: challenges for protecting health information in a new era
B Murdoch - BMC Medical Ethics, 2021 - Springer
Background Advances in healthcare artificial intelligence (AI) are occurring rapidly and there
is a growing discussion about managing its development. Many AI technologies end up …
is a growing discussion about managing its development. Many AI technologies end up …
A transformer-based representation-learning model with unified processing of multimodal input for clinical diagnostics
During the diagnostic process, clinicians leverage multimodal information, such as the chief
complaint, medical images and laboratory test results. Deep-learning models for aiding …
complaint, medical images and laboratory test results. Deep-learning models for aiding …
[HTML][HTML] Chatbot for health care and oncology applications using artificial intelligence and machine learning: systematic review
L Xu, L Sanders, K Li, JCL Chow - JMIR cancer, 2021 - cancer.jmir.org
Background: Chatbot is a timely topic applied in various fields, including medicine and
health care, for human-like knowledge transfer and communication. Machine learning, a …
health care, for human-like knowledge transfer and communication. Machine learning, a …
[HTML][HTML] Medical 4.0 technologies for healthcare: Features, capabilities, and applications
Abstract The Fourth Industrial Revolution may help many sectors and industries, whereas
healthcare will be significantly impacted. Medical advances will be swifter, better and more …
healthcare will be significantly impacted. Medical advances will be swifter, better and more …
Artificial intelligence in US health care delivery
NR Sahni, B Carrus - New England Journal of Medicine, 2023 - Mass Medical Soc
Artificial Intelligence in US Health Care Delivery | New England Journal of Medicine Skip to main
content The New England Journal of Medicine homepage Advanced Search SEARCH …
content The New England Journal of Medicine homepage Advanced Search SEARCH …