The Current and Future State of AI Interpretation of Medical Images | New England Journal of
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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 …

There has been an increasing interest in translating artificial intelligence (AI) research into
clinically-validated applications to improve the performance, capacity, and efficacy of …

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 …

Recent advances in communication technologies and the Internet-of-Medical-Things (IOMT)
have transformed smart healthcare enabled by artificial intelligence (AI). Traditionally, AI …

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 …

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 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 …

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 …

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 …