Artificial Intelligence (AI) In Health Care and Rehabilitation: Difference between revisions
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AI in rehabilitation can augment the patient care by aiding physical therapists in several ways eg providing a thorough assessment, forecasting patients’ performance, establishing a diagnosis. AI in medical and rehabilitation practices can also be applied to problem solving, x-ray diagnosis and protocols for best practice.<ref name=":0" /> | AI in rehabilitation can augment the patient care by aiding physical therapists in several ways eg providing a thorough assessment, forecasting patients’ performance, establishing a diagnosis. AI in medical and rehabilitation practices can also be applied to problem solving, x-ray diagnosis and protocols for best practice.<ref name=":0" /> | ||
== | == Neurology == | ||
Computer-aided diagnosis (CAD) systems using AI and modern signal processing methods have the ability to help clinicians in analyzing and interpreting physiological signals and images more effectively in Neurological Disorders eg epilepsy, Parkinson's disease, Alzheimer's disease, multiple sclerosis, and ischemic brain stroke.<ref>[https://pubmed.ncbi.nlm.nih.gov/31743905/ Raghavendra U, Acharya UR, Adeli H. Artificial intelligence techniques for automated diagnosis of neurological disorders.] European neurology. 2020 Nov 19;82(1-3):41-64.Available: https://pubmed.ncbi.nlm.nih.gov/31743905/<nowiki/>(accessed 4.1.2024)</ref> | |||
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Revision as of 07:36, 4 January 2024
Original Editor - Lucinda hampton
Top Contributors - Lucinda hampton, Ines Musabyemariya and Angeliki Chorti
Introduction[edit | edit source]
Artificial Intelligence (AI) can be viewed as the fourth industrial revolution and the emerging frontier in medicine.[1] AI refers to the capability of a machine to perform a functional task overseen insightfully by humans. AI applies algorithms to learn, think, and then ultimately aide various clinical practices such as eg.radiology and rehabilitation. AI also is used to find current wide scoping clinical information from journals, books, and evidence-based practice, all helping in clinical decision-making in healthcare. Moreover, AI technologies aides in the reduction of medical errors in health care practices.[2]
The emploring of AI technologies is swiftly growing in health care and rehabilitation. As PTs' we need to increase our awareness its manifold applications in rehabilitation to provide best practice patient care.[2]
Sport Medicine/Orthopaedics[edit | edit source]
Current studies looking at the enactment of AI in the areras of orthopaedic surgery and sports medicine show promise in predicting athlete injury risk, the interpretation of medical imaging, evaluating patient-reported outcomes etc. However as with all new knowledge this emerging technology will require a elemental working comprehension of the strengths, limitations, and applications of AI-based tools.[2]
Rehabilitation[edit | edit source]
AI in rehabilitation can augment the patient care by aiding physical therapists in several ways eg providing a thorough assessment, forecasting patients’ performance, establishing a diagnosis. AI in medical and rehabilitation practices can also be applied to problem solving, x-ray diagnosis and protocols for best practice.[2]
Neurology[edit | edit source]
Computer-aided diagnosis (CAD) systems using AI and modern signal processing methods have the ability to help clinicians in analyzing and interpreting physiological signals and images more effectively in Neurological Disorders eg epilepsy, Parkinson's disease, Alzheimer's disease, multiple sclerosis, and ischemic brain stroke.[3]
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References[edit | edit source]
- ↑ Ramkumar PN, Luu BC, Haeberle HS, Karnuta JM, Nwachukwu BU, Williams RJ. Sports medicine and artificial intelligence: a primer. The American Journal of Sports Medicine. 2022 Mar;50(4):1166-74.Available:https://pubmed.ncbi.nlm.nih.gov/33900125/ (accessed 4.1.2024)
- ↑ 2.0 2.1 2.2 2.3 Alsobhi M, Khan F, Chevidikunnan MF, Basuodan R, Shawli L, Neamatallah Z. Physical Therapists’ Knowledge and Attitudes Regarding Artificial Intelligence Applications in Health Care and Rehabilitation: Cross-sectional Study. Journal of Medical Internet Research. 2022 Oct 20;24(10):e39565.Available:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9634519/ (accessed 4.1.2024)
- ↑ Raghavendra U, Acharya UR, Adeli H. Artificial intelligence techniques for automated diagnosis of neurological disorders. European neurology. 2020 Nov 19;82(1-3):41-64.Available: https://pubmed.ncbi.nlm.nih.gov/31743905/(accessed 4.1.2024)
