Manuscript Topics

Recent years have seen a continuous surge of groundbreaking advances in the field of medicine enabled by the use of advanced Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) algorithms. These algorithms leverage data, in the form of electronic health records, high-resolution medical images, bio-signals, genome sequencing data, etc., in order to train predictive models capable of performing a wide range of clinical tasks. The resulting models have shown human-level performance in diagnosis and outcome prediction in a wide variety of diseases ranging from cancers to Alzheimer’s disease, cardiac diseases, stroke, and diabetes, to just name a few.

The present Special Issue aims to cover the latest advances in this area, focusing on the successful applications of AI in diagnosis and prognosis of diseases, as well as methods and strategies to address current limitations including interpretability, generalizability, fairness, and bias. This peer-reviewed Special Issue welcomes contributions in the form of original research articles, review articles, letters, and commentaries.

Keywords
Artificial Intelligence; Clinical Decision Support; Computer Vision; Deep Learning; Electronic Health Records; Machine Learning; Medical Diagnosis; Medical Imaging; Medical Prognosis; Natural Language Processing

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