Unveiling the Influence of AI Predictive Analytics on Patient Outcomes: A Comprehensive Narrative Review.
| Autor: | Dixon D; Medicine, Jubilee Mission Medical College and Research Institute, Thrissur, IND., Sattar H; Medicine, Dow University of Health Sciences, Karachi, PAK., Moros N; Medicine, Pontifical Javeriana University Medical School, Bogotá, COL., Kesireddy SR; Medicine, Sri Venkata Sai Medical College and Hospital, Mahabubnagar, IND., Ahsan H; Medicine, Jinnah Postgraduate Medical Centre, Karachi, PAK., Lakkimsetti M; Medicine, Mamata Medical College, Khammam, IND., Fatima M; Medicine, Fatima Jinnah Medical University, Lahore, PAK., Doshi D; Medicine, Gujarat Cancer Society Medical College, Hospital & Research Centre, Ahmedabad, IND., Sadhu K; Medicine, All India Institute of Medical Sciences, Bathinda, IND., Junaid Hassan M; Internal Medicine, Faisalabad Medical University, Faisalabad, PAK. |
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| Jazyk: | angličtina |
| Zdroj: | Cureus [Cureus] 2024 May 09; Vol. 16 (5), pp. e59954. Date of Electronic Publication: 2024 May 09 (Print Publication: 2024). |
| DOI: | 10.7759/cureus.59954 |
| Abstrakt: | This comprehensive literature review explores the transformative impact of artificial intelligence (AI) predictive analytics on healthcare, particularly in improving patient outcomes regarding disease progression, treatment response, and recovery rates. AI, encompassing capabilities such as learning, problem-solving, and decision-making, is leveraged to predict disease progression, optimize treatment plans, and enhance recovery rates through the analysis of vast datasets, including electronic health records (EHRs), imaging, and genetic data. The utilization of machine learning (ML) and deep learning (DL) techniques in predictive analytics enables personalized medicine by facilitating the early detection of conditions, precision in drug discovery, and the tailoring of treatment to individual patient profiles. Ethical considerations, including data privacy, bias, and accountability, emerge as vital in the responsible implementation of AI in healthcare. The findings underscore the potential of AI predictive analytics in revolutionizing clinical decision-making and healthcare delivery, emphasizing the necessity of ethical guidelines and continuous model validation to ensure its safe and effective use in augmenting human judgment in medical practice. Competing Interests: The authors have declared that no competing interests exist. (Copyright © 2024, Dixon et al.) |
| Databáze: | MEDLINE |
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