A Comparative Study of Machine Learning Model for Early Detection of Heart Failure in Bangladesh: Reducing Disease Burden and Improving Healthcare Services through Data-Driven Knowledge

A Comparative Study of Machine Learning Model for Early Detection of Heart Failure in Bangladesh: Reducing Disease Burden and Improving Healthcare Services through Data-Driven Knowledge | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Comparative Study of Machine Learning Model for Early Detection of Heart Failure in Bangladesh: Reducing Disease Burden and Improving Healthcare Services through Data-Driven Knowledge Mahmood Hasan Khan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7532602/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background: Heart failure (HF) is a leading cause of morbidity and mortality globally. Lower-middle-income countries like Bangladesh are facing difficult challenges in dealing with heart failure due to the unavailability of proper predictive tools, which eventually leads to delayed diagnosis and thus increases the disease burden countrywide. Traditional risk models often fail to capture the intricate interactions between clinical variables. This study investigates the utility of the machine learning (ML) models for predicting heart failure using clinical, demographic, and biomarker data from Bangladeshi subjects. Methods: A cross-sectional observational study was conducted at one of the major hospitals in Dhaka. From face-to-face patient interviews and medical records, a total of 44 features, which include demographic, clinical, laboratory, and imaging data, were extracted. After thorough preprocessing and feature selection using SHAP (Shapely Additive Explanations) values and clinical insight, 15 machine learning algorithms were trained and evaluated using stratified 10-fold cross-validation. Model optimization was performed using Optuna—a powerful hyperparameter framework. Models' performances were evaluated using accuracy, precision, recall, F1 score, and AUC (area under the curve). Results: Among all the models, random forest was found to be the model with the highest mean accuracy of 88.75% and AUC of 92.57% using 10-fold cross-validation after tuning with Optuna. Through SHAP analysis, fractional shortening (FS), left ventricular ejection fraction (LVEF), NYHA class, and BNP (brain natriuretic peptide) were found to be the most significant features. Ensemble methods like bagging and boosting showed slight stability but did not perform any better than the best individual models. The learning and precision-recall curves additionally confirmed model reliability and generalizability. Conclusion: Machine learning models, especially Random Forest and LightGBM, demonstrated high efficiency in the health care settings of Bangladesh. These models offer a promising interpretable tool for early detection of heart failure and thus potentially aid timely intervention in resource-limited settings. Heart failure machine learning Random Forest LightGBM SHAP early diagnosis predictive modeling Full Text Additional Declarations No competing interests reported. Supplementary Files ProductionSheet.xlsx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 17 Oct, 2025 Reviewers agreed at journal 17 Oct, 2025 Reviewers invited by journal 09 Oct, 2025 Editor assigned by journal 07 Oct, 2025 Editor invited by journal 16 Sep, 2025 Submission checks completed at journal 15 Sep, 2025 First submitted to journal 15 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7532602","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":531794484,"identity":"3ba7178b-32cb-4b02-be1a-6fdaf8ee0bcf","order_by":0,"name":"Mahmood Hasan Khan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyUlEQVRIiWNgGAWjYBACNgaGBDCDH0QkFJCiRbIBpMWAFOsMDoBJIlTysTc8e8BQcc9u8/nViR8eGDDI84sdIOAwngPpBgxnipO33Xi7WQLoMMOZsxMIaJFISJNgbEtINrtxdgNIS4LBbWK1GM84u/kHSVrsDPh7txFpC8+BNImEMwkJEjd4t1kkGEgQ9ot8e0+axIeKBHv+/rObb/6osJHnlyaghYGBJwEUmYkNEmCVEoSUgwD7ARBpz8B/gBjVo2AUjIJRMBIBAKnTQAMxEjfbAAAAAElFTkSuQmCC","orcid":"","institution":"Enam Medical College \u0026 Hospital","correspondingAuthor":true,"prefix":"","firstName":"Mahmood","middleName":"Hasan","lastName":"Khan","suffix":""}],"badges":[],"createdAt":"2025-09-04 06:08:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7532602/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7532602/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":94111718,"identity":"5977ced2-baac-4211-8ed0-f463a0e79a94","added_by":"auto","created_at":"2025-10-22 13:30:37","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1075902,"visible":true,"origin":"","legend":"","description":"","filename":"Correctionfile2RevisedManuscriptofDr.MahmoodHasanKhan.docx","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/81543fefbabd00de3ac1fc5c.docx"},{"id":94111717,"identity":"20e73aa9-795e-4112-8b8e-0c9ed51284f6","added_by":"auto","created_at":"2025-10-22 13:30:36","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":731255,"visible":true,"origin":"","legend":"","description":"","filename":"Figer.docx","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/0fab3d8bc18155446cee5422.docx"},{"id":94110865,"identity":"d12a5f90-3b16-4618-bc89-69e12dd6f915","added_by":"auto","created_at":"2025-10-22 13:22:36","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":15861,"visible":true,"origin":"","legend":"","description":"","filename":"Table.docx","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/16fe58051e7a37024e0f5206.docx"},{"id":94110866,"identity":"fd621903-0eff-4311-bbad-3d9bf2e4107b","added_by":"auto","created_at":"2025-10-22 13:22:36","extension":"json","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":5794,"visible":true,"origin":"","legend":"","description":"","filename":"d0424b3b2b5043c5a3b4cddda7727eca.json","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/5b9009b5dbf1c73a3f866dfa.json"},{"id":94113894,"identity":"5a0ae377-9c1e-4cfe-8e79-6c87c0c2b8f8","added_by":"auto","created_at":"2025-10-22 13:54:37","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":19240,"visible":true,"origin":"","legend":"","description":"","filename":"ProductionSheet.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/e22b2878bdf807f077108a4c.xlsx"},{"id":94112280,"identity":"4de3e3ad-ea57-4c18-ba1c-98b1398c5324","added_by":"auto","created_at":"2025-10-22 13:38:37","extension":"xml","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":138187,"visible":true,"origin":"","legend":"","description":"","filename":"d0424b3b2b5043c5a3b4cddda7727eca1enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/24d99e33e44fe3b4d655d36c.xml"},{"id":94110870,"identity":"72129291-9a62-485b-a747-b651943cf6d9","added_by":"auto","created_at":"2025-10-22 13:22:37","extension":"png","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":282982,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/1a01a7b881a552f265dd12c7.png"},{"id":94110871,"identity":"b121df79-eeba-4d81-9bbb-c0fdb31afdee","added_by":"auto","created_at":"2025-10-22 13:22:37","extension":"jpeg","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":321904,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage10.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/a187882efa1b0be2867b213a.jpeg"},{"id":94111721,"identity":"eacb9efa-1792-4ef3-a063-bff20e663880","added_by":"auto","created_at":"2025-10-22 13:30:37","extension":"jpeg","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":330488,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage11.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/4ab2b4ffe4763377457ac560.jpeg"},{"id":94111719,"identity":"2614121a-71ae-4147-8188-4b4eb24af57f","added_by":"auto","created_at":"2025-10-22 13:30:37","extension":"png","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":196389,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage12.png","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/ee4880ec95f03dbbf5bd2b91.png"},{"id":94112281,"identity":"6612f578-4340-4375-9973-d4f345075759","added_by":"auto","created_at":"2025-10-22 13:38:37","extension":"jpeg","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":166900,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage13.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/4115fcf3456f6960c944c236.jpeg"},{"id":94112298,"identity":"cb7b7833-f89b-4d32-9667-f1aee1a991cc","added_by":"auto","created_at":"2025-10-22 13:38:37","extension":"png","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":32484,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage14.png","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/c715de0e4b6abef05501d92d.png"},{"id":94112292,"identity":"7ffae2a0-c276-489e-99da-549c9953ab39","added_by":"auto","created_at":"2025-10-22 13:38:37","extension":"jpeg","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":179126,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage15.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/9452508a276f0c93e18babc0.jpeg"},{"id":94110880,"identity":"8b611ad3-e2bc-4622-b56a-36f59666026c","added_by":"auto","created_at":"2025-10-22 13:22:37","extension":"jpeg","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":305426,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage16.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/b52f534939e7b31560cc4cfd.jpeg"},{"id":94110877,"identity":"a1e1f120-4c1e-43d9-8238-c1fb83375a5e","added_by":"auto","created_at":"2025-10-22 13:22:37","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":66422,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage17.png","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/4f0b9a12fa07323c317ad2b2.png"},{"id":94113895,"identity":"6e02f591-d003-4e23-af74-14868d2f23e8","added_by":"auto","created_at":"2025-10-22 13:54:37","extension":"jpeg","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":321904,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage10.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/5e74e7fc60932537c395c35b.jpeg"},{"id":94112851,"identity":"f31aaac6-370b-4f03-bd76-461db01e6c10","added_by":"auto","created_at":"2025-10-22 13:46:37","extension":"jpeg","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":174691,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/2c5fade06bb0853a2a1fc752.jpeg"},{"id":94112849,"identity":"c8b66e9f-6ded-42dc-b6e0-e98d3b1a9329","added_by":"auto","created_at":"2025-10-22 13:46:37","extension":"jpeg","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":330488,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage11.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/52678293a17bcc33a243c04f.jpeg"},{"id":94110872,"identity":"846eda72-f8ae-470d-99bb-c406ed00ec9f","added_by":"auto","created_at":"2025-10-22 13:22:37","extension":"png","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":196389,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage12.png","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/361b70d2459b06e663852526.png"},{"id":94111729,"identity":"668effae-64b2-4703-8389-c5a4a57bb3cb","added_by":"auto","created_at":"2025-10-22 13:30:37","extension":"jpeg","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":166900,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage13.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/14bd6cdab835d97fe6b835f1.jpeg"},{"id":94111730,"identity":"5df0208d-07fa-4de3-8619-c004f9c4b36d","added_by":"auto","created_at":"2025-10-22 13:30:37","extension":"png","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":32484,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage14.png","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/e368ad62c47fe76bd3f44a5f.png"},{"id":94110894,"identity":"d11d2645-7e42-4d9a-ad35-ede11e65c533","added_by":"auto","created_at":"2025-10-22 13:22:37","extension":"jpeg","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":179126,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage15.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/9f4588ed833dd46040d15d1a.jpeg"},{"id":94112284,"identity":"88236591-b4bf-44a1-84f4-41075279b650","added_by":"auto","created_at":"2025-10-22 13:38:37","extension":"jpeg","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":305426,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage16.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/732aa870ac4a4caab426bd7d.jpeg"},{"id":94110884,"identity":"730d77c6-7e64-47db-b52c-34bb6765b49d","added_by":"auto","created_at":"2025-10-22 13:22:37","extension":"png","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":66422,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage17.png","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/470e2c88401f8d2fdd817f5c.png"},{"id":94112291,"identity":"20dd1896-eae7-45c7-9b55-5b00aee8e364","added_by":"auto","created_at":"2025-10-22 13:38:37","extension":"png","order_by":24,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":57110,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/f5c053aa5e93bc49ddfac9cc.png"},{"id":94111725,"identity":"7dedce6d-f806-4a1f-93b9-13b21a22365e","added_by":"auto","created_at":"2025-10-22 13:30:37","extension":"png","order_by":25,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":47966,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/40afb87d6d5bad81ee48b178.png"},{"id":94110896,"identity":"f15cabdd-0187-404c-8583-9e1aaee101b0","added_by":"auto","created_at":"2025-10-22 13:22:37","extension":"png","order_by":26,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":71330,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage11.png","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/0e40588768271b40d9a2d494.png"},{"id":94112288,"identity":"9713eb9c-751b-452d-8118-6331fc07aca1","added_by":"auto","created_at":"2025-10-22 13:38:37","extension":"png","order_by":27,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":40552,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage12.png","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/224a87d0f14059a972030092.png"},{"id":94113896,"identity":"413f4b6d-cf0b-4c4b-b9be-12ba8e9cb05b","added_by":"auto","created_at":"2025-10-22 13:54:37","extension":"png","order_by":28,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":36763,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage13.png","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/06cd1caf6c745cec36f6af2c.png"},{"id":94112852,"identity":"be97a89b-ca04-40fb-8a5d-9376e0110327","added_by":"auto","created_at":"2025-10-22 13:46:37","extension":"png","order_by":29,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":14679,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage14.png","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/486ba64ff7283df900c43df3.png"},{"id":94110888,"identity":"fbaa9f83-7349-4b31-93ac-53304191a12f","added_by":"auto","created_at":"2025-10-22 13:22:37","extension":"png","order_by":30,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":38193,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage15.png","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/a17f3d70db21bc01e1e0aa58.png"},{"id":94110887,"identity":"0e295cc0-822f-4788-9326-e0ce193aa58c","added_by":"auto","created_at":"2025-10-22 13:22:37","extension":"png","order_by":31,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":47062,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage16.png","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/f7fee4f59b3aabc74bf438dd.png"},{"id":94110898,"identity":"0d4e4449-ffe7-4968-8eba-e1583cc74753","added_by":"auto","created_at":"2025-10-22 13:22:37","extension":"png","order_by":32,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":19239,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage17.png","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/9dd7c6d017cc33c4859e7727.png"},{"id":94110900,"identity":"dda18d2b-37ab-4cbd-8a74-c5eabdf4c6fe","added_by":"auto","created_at":"2025-10-22 13:22:37","extension":"png","order_by":33,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":47966,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage18.png","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/7dcb8050f0e88aac1b396ee6.png"},{"id":94111737,"identity":"7ca1b398-79b1-4cab-a403-35c3ff293105","added_by":"auto","created_at":"2025-10-22 13:30:37","extension":"png","order_by":34,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":59758,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/0f655cae9e66c6857df4f89d.png"},{"id":94111736,"identity":"0eedd4ce-06eb-4b0b-a033-0643cce2f583","added_by":"auto","created_at":"2025-10-22 13:30:37","extension":"png","order_by":35,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":71330,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/4438fcb3aab622feab8560e1.png"},{"id":94110910,"identity":"2659e421-bd65-4732-aa76-2e2a784385fb","added_by":"auto","created_at":"2025-10-22 13:22:38","extension":"png","order_by":36,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":40552,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/bb5494410c0775ff1550f4fc.png"},{"id":94111740,"identity":"3333ef97-831f-4b8b-91bb-8c227770da10","added_by":"auto","created_at":"2025-10-22 13:30:38","extension":"png","order_by":37,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":36763,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/fa3821586d6d19afea291bab.png"},{"id":94110901,"identity":"6cc2039e-44b1-4382-85e7-757adbeb3405","added_by":"auto","created_at":"2025-10-22 13:22:37","extension":"png","order_by":38,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":14679,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage14.png","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/8d0ee4c7d8b90a51db0ab5bd.png"},{"id":94110899,"identity":"8a351dac-0c57-456b-9b2c-9742f84511f9","added_by":"auto","created_at":"2025-10-22 13:22:37","extension":"png","order_by":39,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":38193,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage15.png","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/4fb0c6253de3d4989cb911ea.png"},{"id":94112300,"identity":"ebc55e38-8ab7-4808-99c1-0a6881dc17aa","added_by":"auto","created_at":"2025-10-22 13:38:38","extension":"png","order_by":40,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":47062,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage16.png","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/1b60ea81fa3c33033fbdab88.png"},{"id":94110902,"identity":"80b33ffa-d87d-4538-b947-3322421a0e6b","added_by":"auto","created_at":"2025-10-22 13:22:37","extension":"png","order_by":41,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":19239,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage17.png","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/24190c050553c0efe42260f1.png"},{"id":94110904,"identity":"aef49025-cbed-4c64-bd6d-fd4d102c469f","added_by":"auto","created_at":"2025-10-22 13:22:38","extension":"xml","order_by":42,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":132653,"visible":true,"origin":"","legend":"","description":"","filename":"d0424b3b2b5043c5a3b4cddda7727eca1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/2eba26b48962a5592fb8fccd.xml"},{"id":94112297,"identity":"f2686b97-3096-44a5-b3ad-81f0ec664272","added_by":"auto","created_at":"2025-10-22 13:38:37","extension":"html","order_by":43,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":147208,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/6dab8692370ff682394a0319.html"},{"id":94290399,"identity":"8e2c9cbb-d0c3-43a5-8c98-760d7d6b2091","added_by":"auto","created_at":"2025-10-27 11:15:57","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":918785,"visible":true,"origin":"","legend":"","description":"","filename":"Correctionfile2RevisedManuscriptofDr.MahmoodHasanKhan.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1_covered_adcc5f71-3ed5-46fc-9213-25d7abe5deee.pdf"},{"id":94110868,"identity":"04e8d9ef-791a-451d-8834-4f389529a48e","added_by":"auto","created_at":"2025-10-22 13:22:36","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":19240,"visible":true,"origin":"","legend":"","description":"","filename":"ProductionSheet.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7532602/v1/ff7757d606de428521a512a3.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Comparative Study of Machine Learning Model for Early Detection of Heart Failure in Bangladesh: Reducing Disease Burden and Improving Healthcare Services through Data-Driven Knowledge","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Heart failure, machine learning, Random Forest, LightGBM, SHAP, early diagnosis, predictive modeling","lastPublishedDoi":"10.21203/rs.3.rs-7532602/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7532602/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Heart failure (HF) is a leading cause of morbidity and mortality globally. Lower-middle-income countries like Bangladesh are facing difficult challenges in dealing with heart failure due to the unavailability of proper predictive tools, which eventually leads to delayed diagnosis and thus increases the disease burden countrywide. Traditional risk models often fail to capture the intricate interactions between clinical variables. This study investigates the utility of the machine learning (ML) models for predicting heart failure using clinical, demographic, and biomarker data from Bangladeshi subjects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A cross-sectional observational study was conducted at one of the major hospitals in Dhaka. From face-to-face patient interviews and medical records, a total of 44 features, which include demographic, clinical, laboratory, and imaging data, were extracted. After thorough preprocessing and feature selection using SHAP (Shapely Additive Explanations) values and clinical insight, 15 machine learning algorithms were trained and evaluated using stratified 10-fold cross-validation. Model optimization was performed using Optuna—a powerful hyperparameter framework. Models' performances were evaluated using accuracy, precision, recall, F1 score, and AUC (area under the curve).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Among all the models, random forest was found to be the model with the highest mean accuracy of 88.75% and AUC of 92.57% using 10-fold cross-validation after tuning with Optuna. Through SHAP analysis, fractional shortening (FS), left ventricular ejection fraction (LVEF), NYHA class, and BNP (brain natriuretic peptide) were found to be the most significant features. Ensemble methods like bagging and boosting showed slight stability but did not perform any better than the best individual models. The learning and precision-recall curves additionally confirmed model reliability and generalizability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Machine learning models, especially Random Forest and LightGBM, demonstrated high efficiency in the health care settings of Bangladesh. These models offer a promising interpretable tool for early detection of heart failure and thus potentially aid timely intervention in resource-limited settings.\u003c/p\u003e","manuscriptTitle":"A Comparative Study of Machine Learning Model for Early Detection of Heart Failure in Bangladesh: Reducing Disease Burden and Improving Healthcare Services through Data-Driven Knowledge","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-22 13:22:32","doi":"10.21203/rs.3.rs-7532602/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2025-10-17T20:23:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"102967500605754563666341426898596871761","date":"2025-10-17T20:00:44+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-09T07:12:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-07T14:49:44+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-16T07:31:46+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-15T11:40:29+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cardiovascular Disorders","date":"2025-09-15T11:06:31+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"810c0c34-89e9-4cdc-972d-1888d9b160fa","owner":[],"postedDate":"October 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-10-22T13:22:32+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-22 13:22:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7532602","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7532602","identity":"rs-7532602","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}