Unlocking precision medicine: clinical applications of integrating health records, genetics, and immunology through artificial intelligence
Abstract Artificial intelligence (AI) has emerged as a transformative force in precision medicine, revolutionizing the integration and analysis of health records, genetics, and immunology data. This comprehensive review explores the clinical applications of AI-driven analytics in unlocking personali...
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| Format: | Article |
| Language: | English |
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BMC
2025-02-01
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| Series: | Journal of Biomedical Science |
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| Online Access: | https://doi.org/10.1186/s12929-024-01110-w |
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| author | Yi-Ming Chen Tzu-Hung Hsiao Ching-Heng Lin Yang C. Fann |
| author_facet | Yi-Ming Chen Tzu-Hung Hsiao Ching-Heng Lin Yang C. Fann |
| author_sort | Yi-Ming Chen |
| collection | DOAJ |
| description | Abstract Artificial intelligence (AI) has emerged as a transformative force in precision medicine, revolutionizing the integration and analysis of health records, genetics, and immunology data. This comprehensive review explores the clinical applications of AI-driven analytics in unlocking personalized insights for patients with autoimmune rheumatic diseases. Through the synergistic approach of integrating AI across diverse data sets, clinicians gain a holistic view of patient health and potential risks. Machine learning models excel at identifying high-risk patients, predicting disease activity, and optimizing therapeutic strategies based on clinical, genomic, and immunological profiles. Deep learning techniques have significantly advanced variant calling, pathogenicity prediction, splicing analysis, and MHC-peptide binding predictions in genetics. AI-enabled immunology data analysis, including dimensionality reduction, cell population identification, and sample classification, provides unprecedented insights into complex immune responses. The review highlights real-world examples of AI-driven precision medicine platforms and clinical decision support tools in rheumatology. Evaluation of outcomes demonstrates the clinical benefits and impact of these approaches in revolutionizing patient care. However, challenges such as data quality, privacy, and clinician trust must be navigated for successful implementation. The future of precision medicine lies in the continued research, development, and clinical integration of AI-driven strategies to unlock personalized patient care and drive innovation in rheumatology. |
| format | Article |
| id | doaj-art-79ab2a71bbdd48de95e576d807bc0597 |
| institution | Kabale University |
| issn | 1423-0127 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Biomedical Science |
| spelling | doaj-art-79ab2a71bbdd48de95e576d807bc05972025-02-09T12:48:58ZengBMCJournal of Biomedical Science1423-01272025-02-0132111210.1186/s12929-024-01110-wUnlocking precision medicine: clinical applications of integrating health records, genetics, and immunology through artificial intelligenceYi-Ming Chen0Tzu-Hung Hsiao1Ching-Heng Lin2Yang C. Fann3Division of Allergy, Immunology and Rheumatology, Department of Internal Medicine, Taichung Veterans General HospitalDepartment of Medical Research, Taichung Veterans General HospitalDepartment of Medical Research, Taichung Veterans General HospitalDivision of Intramural Research, National Institute of Neurological Disorders and Stroke, National Institutes of HealthAbstract Artificial intelligence (AI) has emerged as a transformative force in precision medicine, revolutionizing the integration and analysis of health records, genetics, and immunology data. This comprehensive review explores the clinical applications of AI-driven analytics in unlocking personalized insights for patients with autoimmune rheumatic diseases. Through the synergistic approach of integrating AI across diverse data sets, clinicians gain a holistic view of patient health and potential risks. Machine learning models excel at identifying high-risk patients, predicting disease activity, and optimizing therapeutic strategies based on clinical, genomic, and immunological profiles. Deep learning techniques have significantly advanced variant calling, pathogenicity prediction, splicing analysis, and MHC-peptide binding predictions in genetics. AI-enabled immunology data analysis, including dimensionality reduction, cell population identification, and sample classification, provides unprecedented insights into complex immune responses. The review highlights real-world examples of AI-driven precision medicine platforms and clinical decision support tools in rheumatology. Evaluation of outcomes demonstrates the clinical benefits and impact of these approaches in revolutionizing patient care. However, challenges such as data quality, privacy, and clinician trust must be navigated for successful implementation. The future of precision medicine lies in the continued research, development, and clinical integration of AI-driven strategies to unlock personalized patient care and drive innovation in rheumatology.https://doi.org/10.1186/s12929-024-01110-wArtificial intelligencePrecision medicineElectronic health recordsGeneticsImmunologyAutoimmune |
| spellingShingle | Yi-Ming Chen Tzu-Hung Hsiao Ching-Heng Lin Yang C. Fann Unlocking precision medicine: clinical applications of integrating health records, genetics, and immunology through artificial intelligence Journal of Biomedical Science Artificial intelligence Precision medicine Electronic health records Genetics Immunology Autoimmune |
| title | Unlocking precision medicine: clinical applications of integrating health records, genetics, and immunology through artificial intelligence |
| title_full | Unlocking precision medicine: clinical applications of integrating health records, genetics, and immunology through artificial intelligence |
| title_fullStr | Unlocking precision medicine: clinical applications of integrating health records, genetics, and immunology through artificial intelligence |
| title_full_unstemmed | Unlocking precision medicine: clinical applications of integrating health records, genetics, and immunology through artificial intelligence |
| title_short | Unlocking precision medicine: clinical applications of integrating health records, genetics, and immunology through artificial intelligence |
| title_sort | unlocking precision medicine clinical applications of integrating health records genetics and immunology through artificial intelligence |
| topic | Artificial intelligence Precision medicine Electronic health records Genetics Immunology Autoimmune |
| url | https://doi.org/10.1186/s12929-024-01110-w |
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