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Articles

Development and validation of the Sriya Expert Index Plus (SXI++) framework for heart disease prediction and risk reduction through clinical decision support

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By Reeshabh Kumar, Prashant Yadav, Srinivas Kilambi, Mahesh Banavar
| jmai.amegroups.org
Have a website account?Log In orRegister for exclusive website content. Home / Vol 9 (February 28, 2026) / Development and validation of the Sriya Expert Index Plus (SXI++) framework for heart disease prediction and risk reduct... PDF 221 views Full Text 2 views Peer Review File 132 views COI Form 114 views Session Timed Out Your session has expired. Please sign in again.
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Enhancing emergency medical services (EMS) efficiency: design and validation of an SXI++ large numerical model (LNM) for response time prediction

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By Prashant Kumar Yadav, Reeshabh Kumar, Mahesh Banavar, Srinivas Kilambi
| jmai.amegroups.org
Have a website account?Log In orRegister for exclusive website content. Home / Vol 9 (February 28, 2026) / Enhancing emergency medical services (EMS) efficiency: design and validation of an SXI++ large numerical model (LNM) for... Session Timed Out Your session has expired. Please sign in again.
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Performance Evaluation of SXI++ and Comparative Triage Machine Learning Models for Enhanced Medical Decision-Making

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By Mahesh Banavar, Reeshabh Kumar, Prashant Yadav, Devarpita Dey
| preprints.org
Submitted: 16 September 2025 Posted: 18 September 2025 You are already at the latest version Effective triage is vital to prioritize patient care and optimize resource utilization. This study compares traditional machine learning, represented by an XGBoost classifier, with SXI++, a proprietary deep neural network and ensemble learning framework, for predicting Emergency Severity Index (ESI) levels.
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