Machine Learning for Healthcare Applications
A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Health Care Sciences & Services".
Deadline for manuscript submissions: closed (30 March 2023) | Viewed by 7388
Special Issue Editor
Special Issue Information
Dear Colleagues,
When I was a student studying computer science in the 1980s, I took a course in artificial intelligence. I was deeply disappointed. In those days, AI involved building a list of rules. For example, if a patient presents with a cough, high fever, and trouble smelling, then he or she probably has COVID-19. Duh. Plus, we had to program in LISP, which eschewed iteration in favor of recursion. Very strange. They said that AI was going to become mainstream in five years. It was always five years in the future. However, now, some forty years on, with the recent development of neural networks programmed with Python, AI is finally showing its potential. Instead of a list of rules, the network is trained on previously obtained data. The data can be in the form of images or test results. For example, a neural network can be trained to detect likely COVID-19 cases by feeding it a list of labeled normal and positive case data. The trained network can then be used to detect cases that might otherwise be overlooked by humans. Beyond diagnosis, AI is showing promise in various fields of medicine, from individualized medication to hospital management; software tools based on artificial neural networks are being developed to assist doctors and staff. We hope that this Special Issue will introduce a variety of these recent developments of AI in public health.
Dr. Kenneth Lee Sutherland
Guest Editor
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Keywords
- automated disease diagnosis
- telemedicine
- medical imaging
- smart health monitoring
- social media healthcare
- machine learning for COVID-19
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