Vasanthakumar, G. U. and Dankan Gowda, V. and Manage, Prabhakar S. and Prasad, K. D. V. and Hariram, Venkatesan (2024) Electronic Health Records (EHR) and Clinical Decision Support Systems. Springer. pp. 277-302. ISSN 2326-4136
Full text not available from this repository.Abstract
The extensive use of clinical decision support systems (CDSS) and electronic health records (EHR) has significantly altered the landscape of healthcare. Medical professionals now have access to priceless tools that transform patient data management and help them make wise clinical judgments. However, as we seamlessly incorporate artificial intelligence (AI) solutions into EHR and CDSS, a new era of healthcare is beginning. The incorporation of AI technologies is thoroughly explored in this chapter, shedding light on how they might improve clinical operations and patient outcomes. The chapter opens by emphasizing the crucial role played by EHR in centralizing medical records, digitizing patient data, and enabling effective data sharing between healthcare providers. The chapter conducts an in-depth exploration of how machine learning algorithms are applied to unearth patterns in patient data, identify disease risks, and provide personalized treatment recommendations. © 2024 Elsevier B.V., All rights reserved.
| Item Type: | Article |
|---|---|
| Subjects: | Health Professions > Health Information Management |
| Divisions: | Medicine > Vinayaka Mission's Kirupananda Variyar Medical College and Hospital, Salem |
| Depositing User: | Unnamed user with email techsupport@mosys.org |
| Last Modified: | 27 Nov 2025 06:33 |
| URI: | https://vmuir.mosys.org/id/eprint/1683 |
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