ISSN2320-2882
Impact Factor9.17
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CrossRefDOI
ESTD2013
Peer ReviewTransparent
AccessOpen
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Paper Title
Explainable Multimodal Machine Learning Framework for Early Disease Risk Prediction
Authors
Harjas Singh , Palak Khurana , Dr alpana jijja
Keywords
Machine Learning, Multimodal Learning, Explainable AI, Healthcare Analytics, Disease Risk Prediction
Abstract
Early disease risk prediction is essential for effective preventive healthcare. This paper presents an explainable multimodal machine learning framework that integrates clinical and lifestyle data for improved prediction accuracy. Models such as Logistic Regression, Random Forest, and Support Vector Machine are evaluated using metrics like accuracy and ROC-AUC. To enhance interpretability, SHAP is used to explain feature contributions. The results show that combining multimodal data with explainable AI improves both prediction performance and model transparency.
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IJCRT — journal style
"Explainable Multimodal Machine Learning Framework for Early Disease Risk Prediction", IJCRT - International Journal of Creative Research Thoughts (www.ijcrt.org), ISSN:2320-2882, Vol.14, Issue 4, page no.m111-m115, April 2026, Available :https://ijcrt.org/papers/IJCRT26A4408.pdf
APA — 7th edition
Singh, H., Khurana, P., & jijja, A. (2026). Explainable Multimodal Machine Learning Framework for Early Disease Risk Prediction. International Journal of Creative Research Thoughts, 14(4), m111-m115. https://doi.org/10.56975/ijcrt.v14i4.307144
MLA — 9th edition
Singh, Harjas, et al. "Explainable Multimodal Machine Learning Framework for Early Disease Risk Prediction." International Journal of Creative Research Thoughts, vol. 14, no. 4, 2026, pp. m111-m115, https://doi.org/10.56975/ijcrt.v14i4.307144.
Chicago — 17th, bibliography
Singh, Harjas, Palak Khurana, and alpana jijja. "Explainable Multimodal Machine Learning Framework for Early Disease Risk Prediction." International Journal of Creative Research Thoughts 14, no. 4 (2026): m111-m115. https://doi.org/10.56975/ijcrt.v14i4.307144.
Harvard — author–date
Singh, H., Khurana, P. and jijja, A. (2026) 'Explainable Multimodal Machine Learning Framework for Early Disease Risk Prediction', International Journal of Creative Research Thoughts, 14(4), pp. m111-m115. Available at: https://doi.org/10.56975/ijcrt.v14i4.307144
IEEE — numbered reference
H. Singh, P. Khurana and A. jijja, "Explainable Multimodal Machine Learning Framework for Early Disease Risk Prediction," IJCRT, vol. 14, no. 4, pp. m111-m115, Apr. 2026, doi: 10.56975/ijcrt.v14i4.307144.
Vancouver — biomedical
Singh H, Khurana P, jijja A. Explainable Multimodal Machine Learning Framework for Early Disease Risk Prediction. IJCRT. 2026 Apr;14(4):m111-m115. doi: 10.56975/ijcrt.v14i4.307144
AMA — 11th edition
Singh H, Khurana P, jijja A. Explainable Multimodal Machine Learning Framework for Early Disease Risk Prediction. IJCRT. 2026;14(4):m111-m115. doi:10.56975/ijcrt.v14i4.307144
BibTeX — Zotero, Mendeley, LaTeX
@article{IJCRT26A4408,
author = {Harjas Singh and Palak Khurana and alpana jijja},
title = {Explainable Multimodal Machine Learning Framework for Early Disease Risk Prediction},
journal = {International Journal of Creative Research Thoughts},
volume = {14},
number = {4},
pages = {m111-m115},
year = {2026},
month = {April},
issn = {2320-2882},
doi = {10.56975/ijcrt.v14i4.307144},
url = {https://doi.org/10.56975/ijcrt.v14i4.307144}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - Singh, Harjas
AU - Khurana, Palak
AU - jijja, alpana
TI - Explainable Multimodal Machine Learning Framework for Early Disease Risk Prediction
T2 - International Journal of Creative Research Thoughts
JA - IJCRT
VL - 14
IS - 4
PY - 2026
SN - 2320-2882
DO - 10.56975/ijcrt.v14i4.307144
UR - https://doi.org/10.56975/ijcrt.v14i4.307144
SP - m111-m115
ER -
Issue
Volume 14 Issue 4,
April-2026
Pages : m111-m115
Article Information
- Pages
- m111-m115
- Published
- April 2026
- Registration ID
- IJCRT_307144
- Published Paper ID
- IJCRT26A4408
- Research Area
- Science and Technology
- Author Type
- Indian Author
- Location
- Delhi, Delhi, India
- Peer Review
- Request Peer Review Report
- Licence
- CC BY 4.0 · Open Access
- ISSN & Impact Factor
- 2320-2882 · IF 9.17
- Downloads
- 157
- Permanent Link
- https://ijcrt.org/viewpaperforall.php?paper=IJCRT26A4408
- Published Paper PDF
- https://ijcrt.org/papers/IJCRT26A4408.pdf
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International Journal of Creative Research Thoughts
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2320-2882
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The authors would like to thank the reviewers and the editorial board of International Journal of Creative Research Thoughts for their careful reading and constructive comments, and all colleagues who supported the preparation of this manuscript.
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