Artificial intelligence-enabled healthcare delivery

By Sandeep Reddy, John Fox, M. Purohit. Journal of the Royal Society of Medicine, 2018

462 citations recorded by the source corpus.

Summary In recent years, there has been massive progress in artificial intelligence (AI) with the development of deep neural networks, natural language processing, computer vision and robotics. These techniques are now actively being applied in healthcare with many of the health service activities currently being delivered by clinicians and administrators predicted to be taken over by AI in the coming years. However, there has also been exceptional hype about the abilities of AI with a mistaken notion that AI will replace human clinicians altogether. These perspectives are inaccurate, and if a balanced perspective of the limitations and promise of AI is taken, one can gauge which parts of the health system AI can be integrated to make a meaningful impact. The four main areas where AI would have the most influence would be: patient administration, clinical decision support, patient monitoring and healthcare interventions. This health system where AI plays a central role could be termed an AI-enabled or AI-augmented health system. In this article, we discuss how this system can be developed based on a realistic assessment of current AI technologies and predicted developments.

Subfields: Artificial Intelligence, Health Informatics, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/ad680d13cd06ea8a8722d1da1121f105277adb73

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In Artificial Intelligence

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Citations in the corpus

A governance model for the application of AI in health care (2019, background): “1,2,7,13,17 Clinical use of AI models is certain to transform current models of healthcare delivery; indeed, their reach will extend beyond clinical settings.”
Generative AI in healthcare: an implementation science informed translational path on application, integration and governance (2024, background): “Artificial intelligence (AI) has become an increasingly popular tool in a variety of fields, including healthcare, with the potential to transform clinical decision-making and improve health outcomes [1–3].”
The Recent Progress and Applications of Digital Technologies in Healthcare: A Review (2020, background): “One of the promising and rapidly growing modern trends is the use of the capabilities of AI and Machine Learning (ML) in healthcare, including the diagnosis and treatment of a number of diseases [9, 10].”
Artificial Intelligence for Mental Health and Mental Illnesses: An Overview (2019, background): “AI is currently being used to facilitate early disease detection, enable better understanding of disease progression, optimize medication/treatment dosages, and uncover novel treatments [8, 10 – 13, 14 (cid:129)(cid:129) , 15].”
Communication-Efficient Edge AI: Algorithms and Systems (2020, background): “For example, AI technologies have shown promises in healthcare [25], such as detection of heart failure [26] with recurrent neural network (RNN) and decisions about patient treatment [27] with reinforcement learning.”
Use of AI-based tools for healthcare purposes: a survey study from consumers’ perspectives (2020, background): “For instance, it will create a risky situation for both clinicians and patients when it is still not clear who becomes responsible if AI-based tools offer wrong recommendations in healthcare [29].”