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Text Nailing, an alternative approach to machine learning, capable of extracting features from clinical narrative notes was introduced in 2017. This technique has been applied to the search for novel drug targets, as this task requires the examination of information stored in biological databases and journals. [ 59 ]
A pioneer in the use of artificial intelligence in healthcare was American biomedical informatician Edward H. Shortliffe. This field deals with utilization of machine-learning algorithms and artificial intelligence, to emulate human cognition in the analysis, interpretation, and comprehension of complicated medical and healthcare data.
The Journal of Clinical Microbiology is a monthly medical journal published by the American Society for Microbiology. The journal was established in 1975. The editor-in-chief is Alexander J. McAdam (Boston Children's Hospital). It is a delayed open access journal. Full text content is available free after a six-month embargo.
Artificial intelligence in pharmacy is the application of artificial intelligence (AI) [117] [118] [119] to the discovery, development, and the treatment of patients with medications. [120] AI in pharmacy practices has the potential to revolutionize all aspects of pharmaceutical research as well as to improve the clinical application of ...
The Journal of Allergy and Clinical Immunology; Journal of the American College of Cardiology; Journal of the American Medical Directors Association; Journal of the American Society for Mass Spectrometry; Journal of Anthropological Archaeology; Journal of Applied Economics; Journal of Approximation Theory; Journal of the Association of Nurses ...
Arthroscopy (journal) Artificial Intelligence (journal) Asian Journal of Social Science; ... Clinical Microbiology and Infection; Clinical Neurology and Neurosurgery;
This is a list of notable peer-reviewed scientific journals that focus on bioinformatics and computational biology. BioData Mining; Bioinformatics;
Integration of Artificial Intelligence: While AI offers significant potential to enhance diagnostic accuracy and efficiency in imaging, its integration into clinical workflows is fraught with challenges. These include the need for high-quality, annotated datasets for training AI models, the risk of algorithmic bias, and the black-box nature of ...
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