{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T09:07:08Z","timestamp":1788944828075,"version":"build-2803163510"},"reference-count":31,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T00:00:00Z","timestamp":1788739200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Background\/Objectives: Cardiovascular diseases (CVDs) represent the foremost public health challenge of recent days. According to the World Health Organization (WHO), nearly 32% of people die from CVDs each year. This paper introduces a quantum-inspired, information-theoretic framework for comparing CVD risk-factor architectures in modeled Indian and global populations. Methods: Each synthetic population is represented as a population state matrix (\u03c1) built from discretized epidemiological variables (age, sex, smoking, diabetes, hypertension, and dyslipidemia). Systemic uncertainty is quantified with von Neumann entropy (equivalent to Shannon entropy for diagonal states), inter-factor dependence with Systemic Mutual Information (SMI), and synthetic population similarity with Uhlmann fidelity. Results: In illustrative modeled scenarios (N=10,000 synthetic profiles per synthetic population), diabetes entropy is higher in the Indian comparator (0.88 vs. 0.61 bits), diabetes\u2013hypertension SMI is larger in India (\u22480.46 vs. 0.22 bits), and smoking\u2013hypertension dependence is stronger globally (0.36 vs. 0.21 bits). Overall fidelity is F\u22480.76. Conclusions: These results are hypothesis-generating point estimates and require clinical data verification on harmonized synthetic individual-level data before clinical or policy use. This study represents a quantum information-theoretic framework for comparing modeled CVD risk profiles. Illustrative results suggest stronger diabetes\u2013hypertension dependence in the Indian scenario and stronger smoking\u2013hypertension dependence in the global comparator.<\/jats:p>","DOI":"10.3390\/diagnostics16172878","type":"journal-article","created":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T13:53:28Z","timestamp":1788789208000},"page":"2878","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Synthetic Comparative Analysis of Cardiovascular Disease Profiles Using Quantum Information Measures in Indian and Global Populations"],"prefix":"10.3390","volume":"16","author":[{"given":"Santosh Kumar","family":"Sahoo","sequence":"first","affiliation":[{"name":"School of Computing Science and Engineering, VIT Bhopal University, Sehore 466114, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sumant Kumar","family":"Mohapatra","sequence":"additional","affiliation":[{"name":"Department of CSE (AI&ML), School of Engineering, Dayananda Sagar University, Bengaluru 562112, India"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"software","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"}]},{"given":"Srikanta Kumar","family":"Mohapatra","sequence":"additional","affiliation":[{"name":"Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura 140401, Punjab, India"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"investigation","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2322-7289","authenticated-orcid":false,"given":"Chander","family":"Prabha","sequence":"additional","affiliation":[{"name":"Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura 140401, Punjab, India"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"}]},{"given":"Jayashree","family":"Mohanty","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Chandigarh University, Mohali 140413, India"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"}]},{"given":"Deepudev","family":"Sahadevan","sequence":"additional","affiliation":[{"name":"Faculty of Mathematics and Data Sciences, Emirates Aviation University, Dubai P.O. Box 53044, United Arab Emirates"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"project-administration","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"}]},{"given":"Sumendra","family":"Yogarayan","sequence":"additional","affiliation":[{"name":"Faculty of Information Science and Technology (FIST), Multimedia University (MMU), Jalan Ayer Keroh Lama, Bukit Beruang, Ayer Keroh 75450, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Balamurugan","family":"Balusamy","sequence":"additional","affiliation":[{"name":"School of Engineering and IT, Manipal Academy of Higher Education, Dubai Campus, Dubai P.O. 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