The Future of Artificial Intelligence in Clinical Medicine

Dear Colleagues,

Artificial intelligence (AI) is the ability of computers to accomplish tasks that are normally completed by intelligent beings such as humans and animals. Among current AI applications, machine learning (ML) is a tool that combines computer science with statistics for generating advanced algorithms capable of identifying the complex relationships within large datasets. At present, ML is being applied in numerous fields of modern society, including web searching, social media networking, and facial recognition. In medicine, ML has shown impressive diagnostic skills through imaging analysis with potential applicability in radiology, pathology, and dermatology. For example, in a recent study, ML algorithms performed better than experienced dermatologists at detecting skin cancer. Similarly, the C-Path tool, an automated pathologist algorithm that used unsupervised ML and automated image processing to identify thousands of novel imaging features successfully identified high-risk breast cancers. In addition, based on chest X-ray images, deep learning algorithms showed remarkable precision and accuracy in the diagnosis of tuberculosis. These examples provide proof of concept for ML use in medicine. However, the feasibility of this approach in everyday clinical practice is unknown and requires further validation. Nevertheless, with the new advancements in computer processing power and the exponential growth of digital health data, there is growing enthusiasm for the potential utilization of ML in clinical medicine. This Special Issue will highlight recent advances in the diverse utilization of AI tools in clinical medicine. We welcome the submission of original research articles encompassing both preclinical and clinical studies, as well as review and opinion articles that include, but are not limited to, the following aspects: (1) artificial intelligence in medical practice; (2) artificial intelligence in medicine ethical considerations; (3) diagnostic applications of artificial intelligence; (4) predicting infection complications with artificial intelligence; (5) cancer and artificial intelligence; (6) predicting patients’ survival with artificial intelligence; and (7) artificial intelligence for interpreting radiographic images: friend or foe?

Dr. Luis Espinoza
Guest Editor

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