American International Journal of Advanced Research and Development

E-ISSN: XXXX-XXXX   •   Impact Factor: -

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 8, Issue 5 (September-October 2026) Submit your research before last 3 days of October to publish your research paper in the issue of September-October.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 8 Issue 5
September-October 2026

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

Healthcare Data Analytics for Intelligent Medical Decision-Making

Author(s) Marco Spruit
Country Netherlands
Abstract Healthcare data analytics has become an important component of modern healthcare systems because of the increasing availability of electronic health records, medical imaging, laboratory information, wearable-device data, clinical documentation, and other digital health information. The effective analysis of these diverse datasets can support intelligent medical decision-making by identifying patterns, predicting risks, improving patient monitoring, and providing evidence-based information to healthcare professionals. This study examines healthcare data analytics for intelligent medical decision-making through a conceptual and literature-based research approach. The study focuses on descriptive analytics, predictive analytics, prescriptive analytics, machine learning, artificial intelligence, clinical decision-support systems, data integration, and patient-centered analytical applications. The analysis indicates that healthcare data analytics can contribute to clinical risk assessment, disease prediction, patient monitoring, diagnostic support, treatment planning, and healthcare resource management. Descriptive analytics can summarize existing healthcare information, predictive analytics can estimate potential outcomes, and prescriptive approaches can provide decision-support recommendations.
Machine-learning and artificial-intelligence techniques can further improve the processing of complex healthcare datasets. However, effective implementation is constrained by data quality, interoperability, privacy, cybersecurity, algorithmic bias, explainability, infrastructure limitations, and professional acceptance. Healthcare analytics should therefore be integrated with clinical expertise rather than treated as an independent decision-making mechanism. Appropriate governance, data standards, secure infrastructure, transparent analytical processes, and continuous validation are essential for reliable implementation. The study concludes that healthcare data analytics can strengthen intelligent medical decision-making by transforming complex healthcare information into structured analytical insights. Future research should emphasize explainable analytics, multimodal data integration, privacy-preserving computation, real-time decision support, personalized healthcare analytics, and human-AI collaboration to develop reliable, secure, and patient-centered intelligent healthcare environments.
Keywords Healthcare Data Analytics, Medical Decision-Making, Predictive Analytics, Clinical Decision Support, Artificial Intelligence, Machine Learning, Electronic Health Records, Healthcare Informatics, Patient Monitoring, Digital Health
Field Engineering
Published In Volume 5, Issue 2, March-April 2023
Published On 2023-04-10
View / Download PDF File

Share this



E-ISSN XXXX-XXXX
CrossRef

CrossRef DOI prefix of AIJARD is 10.00000/AIJARD

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About AIJARD
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +1-872-302-3851 editor@aijard.com