Advances in Generating Real-World Evidence from Real-World Data Using Artificial Intelligence

Dear Colleagues,

Real-world evidence (RWE) consists of evidence on patient care and health outcomes that has been developed from real-world data (RWD) generated in routine clinical settings. Its uses span clinical and regulatory decision-making, health technology assessment, clinical trial design, assessing the burden of illness, evaluating market potential for new products, etc. The wide usage of the internet, social media, wearable sensors, mobile devices, electronic billing, disease and product registries, electronic health records and other technology-driven services, together with increased capacity in data storage, have led to the rapid generation and availability of vast amounts of RWD. The increasing accessibility of RWD and the fast development of artificial intelligence (AI) and machine learning (ML) techniques, together with rising costs and the recognized limitations of traditional trials, has spurred great interest in the use of RWD to enhance the efficiency of clinical research and discoveries, and bridge the evidence gap between clinical research and practice. Modern AI approaches have significant potential in generating RWE from complex multimodal data. However, the generation of high-quality RWE using AI faces a spectrum of challenges such as data quality, heterogeneity and completeness, selection bias and generalizability, temporal drifts of longitudinal data, ethical and privacy concerns, regulatory acceptance and validation, and explainability.

This Special Issue will invite original articles, reviews and commentaries representing the best practices and current advances in AI applications for RWE generation, as well as discussions on approaches to address existing challenges.

Prof. Dr. Joseph Finkelstein
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• real-world evidence
• artificial intelligence
• healthcare