Recently clinicians have become more reliant on technologies such as artificial intelligence (AI) and machine learning (ML) for effective and accurate diagnosis and prognosis of diseases, especially mental health disorders. These remarks, however, ap...
Rapid advancements in artificial intelligence and machine learning (AI/ML) in healthcare raise pressing questions about how much users should trust AI/ML systems, particularly for high stakes clinical decision-making. Ensuring that user trust is prop...
With the introduction of artificial intelligence (AI) to healthcare, there is also a need for professional guidance to support its use. New (2022) reports from National Health Service AI Lab & Health Education England focus on healthcare workers' und...
I discuss an influential argument put forward by Hatherley in the Drawing on influential philosophical accounts of interpersonal trust, Hatherley claims that medical artificial intelligence is capable of being reliable, but not trustworthy. Furtherm...
Components of artificial intelligence (AI) for analysing social big data, such as natural language processing (NLP) algorithms, have improved the timeliness and robustness of health data. NLP techniques have been implemented to analyse large volumes ...
Obtaining informed consent from patients prior to a medical or surgical procedure is a fundamental part of safe and ethical clinical practice. Currently, it is routine for a significant part of the consent process to be delegated to members of the cl...
Digitalisation of health and the use of health data in artificial intelligence, and machine learning (ML), including for applications that will then in turn be used in healthcare are major themes permeating current UK and other countries' healthcare ...