The current and future state of AI interpretation of medical images
P Rajpurkar, MP Lungren - New England Journal of Medicine, 2023 - Mass Medical Soc
The Current and Future State of AI Interpretation of Medical Images | New England Journal of
Medicine Skip to main content The New England Journal of Medicine homepage Advanced …
Medicine Skip to main content The New England Journal of Medicine homepage Advanced …
Algorithmic fairness in artificial intelligence for medicine and healthcare
In healthcare, the development and deployment of insufficiently fair systems of artificial
intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models …
intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models …
A full dive into realizing the edge-enabled metaverse: Visions, enabling technologies, and challenges
Dubbed “the successor to the mobile Internet,” the concept of the Metaverse has grown in
popularity. While there exist lite versions of the Metaverse today, they are still far from …
popularity. While there exist lite versions of the Metaverse today, they are still far from …
[HTML][HTML] Privacy-preserving artificial intelligence in healthcare: Techniques and applications
There has been an increasing interest in translating artificial intelligence (AI) research into
clinically-validated applications to improve the performance, capacity, and efficacy of …
clinically-validated applications to improve the performance, capacity, and efficacy of …
Federated learning for smart healthcare: A survey
Recent advances in communication technologies and the Internet-of-Medical-Things (IOMT)
have transformed smart healthcare enabled by artificial intelligence (AI). Traditionally, AI …
have transformed smart healthcare enabled by artificial intelligence (AI). Traditionally, AI …
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 …
Multimodal integration of radiology, pathology and genomics for prediction of response to PD-(L) 1 blockade in patients with non-small cell lung cancer
Immunotherapy is used to treat almost all patients with advanced non-small cell lung cancer
(NSCLC); however, identifying robust predictive biomarkers remains challenging. Here we …
(NSCLC); however, identifying robust predictive biomarkers remains challenging. Here we …
Federated learning for healthcare: Systematic review and architecture proposal
The use of machine learning (ML) with electronic health records (EHR) is growing in
popularity as a means to extract knowledge that can improve the decision-making process in …
popularity as a means to extract knowledge that can improve the decision-making process in …
Predicting cancer outcomes with radiomics and artificial intelligence in radiology
The successful use of artificial intelligence (AI) for diagnostic purposes has prompted the
application of AI-based cancer imaging analysis to address other, more complex, clinical …
application of AI-based cancer imaging analysis to address other, more complex, clinical …
Federated learning for predicting histological response to neoadjuvant chemotherapy in triple-negative breast cancer
J Ogier du Terrail, A Leopold, C Joly, C Béguier… - Nature medicine, 2023 - nature.com
Triple-negative breast cancer (TNBC) is a rare cancer, characterized by high metastatic
potential and poor prognosis, and has limited treatment options. The current standard of …
potential and poor prognosis, and has limited treatment options. The current standard of …