Artificial intelligence (AI) is a new technical discipline that uses computer technology to research and develop the theory, method, technique, and application system for the simulation, extension, and expansion of human intelligence. With the assistance of new AI technology, the traditional medical environment has changed a lot. For example, a patient's diagnosis based on radiological, pathological, endoscopic, ultrasonographic, and biochemical examinations has been effectively promoted with a higher accuracy and a lower human workload. The medical treatments during the perioperative period, including the preoperative preparation, surgical period, and postoperative recovery period, have been significantly enhanced with better surgical effects. In addition, AI technology has also played a crucial role in medical drug production, medical management, and medical education, taking them into a new direction. The purpose of this review is to introduce the application of AI in medicine and to provide an outlook of future trends.
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http://dx.doi.org/10.1007/s11596-021-2474-3 | DOI Listing |
Clin Chem Lab Med
January 2025
Section of Clinical Biochemistry, University of Verona, Verona, Italy.
J Med Internet Res
January 2025
Chronic Disease Epidemiology, Population and Public Health, Pennington Biomedical Research Center, Baton Rouge, LA, United States.
Background: Electronic health records (EHRs) facilitate the accessibility and sharing of patient data among various health care providers, contributing to more coordinated and efficient care.
Objective: This study aimed to summarize the evolution of secondary use of EHRs and their interoperability in medical research over the past 25 years.
Methods: We conducted an extensive literature search in the PubMed, Scopus, and Web of Science databases using the keywords Electronic health record and Electronic medical record in the title or abstract and Medical research in all fields from 2000 to 2024.
J Med Internet Res
January 2025
Institute for Entrepreneurship, Technology Management and Innovation (EnTechnon), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
Background: Digital health technology (DHT) has the potential to revolutionize the health care industry by reducing costs and improving the quality of care in a sector that faces significant challenges. However, the health care industry is complex, involving numerous stakeholders, and subject to extensive regulation. Within the European Union, medical device regulations impose stringent requirements on various ventures.
View Article and Find Full Text PDFJMIR Public Health Surveill
January 2025
Laboratoire AGEIS, Université Grenoble Alpes, La Tronche Cedex, France.
Background: Although agricultural health has gained importance, to date, much of the existing research relies on traditional epidemiological approaches that often face limitations related to sample size, geographic scope, temporal coverage, and the range of health events examined. To address these challenges, a complementary approach involves leveraging and reusing data beyond its original purpose. Administrative health databases (AHDs) are increasingly reused in population-based research and digital public health, especially for populations such as farmers, who face distinct environmental risks.
View Article and Find Full Text PDFJ Speech Lang Hear Res
January 2025
Department of Psychology, University of Western Ontario, London, Canada.
Purpose: Recent advances in artificial intelligence provide opportunities to capture and represent complex features of human language in a more automated manner, offering potential means of improving the efficiency of language assessment. This review article presents computerized approaches for the analysis of narrative language and identification of language disorders in children.
Method: We first describe the current barriers to clinicians' use of language sample analysis, narrative language sampling approaches, and the data processing stages that precede analysis.
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