International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Smart Health Care |
|---|---|
| ABSTRACT | Digital healthcare systems have grown rapidly in recent years, increasing the need for reliable and understandable diagnostic tools. Although machine learning improves prediction accuracy, many models still lack transparency, making them difficult to trust in healthcare environments. This paper presents a Smart Healthcare System that combines machine learning with rule-based reasoning to provide both accurate and explainable predictions. TF-IDF and Multinomial Naïve Bayes are used for symptom analysis and disease prediction, while the reasoning engine generates explanations and suggestions for users. The system is implemented using Flask and MongoDB with a simple user interface. Experimental results achieved an F1-score of 0.86, showing good performance and usability. The proposed approach can support telemedicine and rural healthcare by providing quick and understandable decision support. |
| AUTHOR | SHRUTI BORADE, PURVA DOSHI, JINAL LODHA, CHINTAL GALA, ARUNA KADAM Department of Information Technology, Shah & Anchor Kutchhi Engineering College, Mumbai, India |
| VOLUME | 184 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1405044 |
| pdf/44_Smart Health Care.pdf | |
| KEYWORDS | |
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