Gaining knowledge and actionable insights from complex, high-dimensional and
heterogeneous biomedical data remains a key challenge in transforming health care …

Despite the recent developments in deep learning models, their applications in clinical
decision-support systems have been very limited. Recent digitalisation of health records …

There is a growing focus on making clinical trials more inclusive but the design of trial
eligibility criteria remains challenging,–. Here we systematically evaluate the effect of …

Secondary use of electronic health records (EHRs) promises to advance clinical research
and better inform clinical decision making. Challenges in summarizing and representing …

Objective The objective of this study is to systematically examine the efficacy of both
proprietary (GPT-3.5, GPT-4) and open-source large language models (LLMs)(LLAMA 7B …

The 21st Century Cures Act passed by the United States Congress mandates the US Food
and Drug Administration to develop guidance to evaluate the use of real‐world evidence …

Background and objective Clinical trials are of high importance for medical progress. This
study conducted a systematic review to identify the applications of EHRs in supporting and …

This Perspective provides examples of current and future applications of deep learning in
pharmacogenomics, including: identification of novel regulatory variants located in …

Background Recruiting and retaining participants in randomised controlled trials (RCTs) is
challenging. Digital tools, such as social media, data mining, email or text-messaging, could …

How can we interpret and retrieve medical evidence to support clinical decisions? Clinical
trial reports (CTR) amassed over the years contain indispensable information for the …