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The article presents the discussion on Machine learning (ML) having highly transformative approaches to the automation of numerous clinical tasks. Topics include computer scientists being most concerned with demonstrating the superiority of ML-driven systems at performing classificatory or predictive tasks; and focusing on ensuring the safety and effectiveness of medical devices, software, and drugs before receiving market authorization.

The article discusses digital medicine's definition as a device technology and medication combination in the article by Klugman et al. in 2018. Topics covered include questions on the digital medicine and digital health difference, digital medicine's alternative definition as the subset of digital products, and the quest for solid evidence on the effectivity of digital medicine solutions. Also noted is the ethical significance of the semantic ambiguity of digital health and digital medicine.

The article talks about informed consent of the participants in medical research and the disclosure of clinical results to the participants. Topics discussed include the field of genomic research, the patients undergoing genome sequencing and seeking information on the incidental findings, and the concept of the disclosure of results being a right of the patients.