首页|New Kidney Disease Study Findings Have Been Reported by Researchersat SRM Unive rsity (Enhancing Machine Learning-basedForecasting of Chronic Renal Disease Wit h Ai)
New Kidney Disease Study Findings Have Been Reported by Researchersat SRM Unive rsity (Enhancing Machine Learning-basedForecasting of Chronic Renal Disease Wit h Ai)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Research findings on Kidney Diseases a nd Conditions - Kidney Disease are discussedin a new report. According to news reporting out of Andhra Pradesh, India, by NewsRx editors, researchstated, “Chr onic renal disease (CRD) is a significant concern in the field of healthcare, hi ghlighting thecrucial need of early and accurate prediction in order to provide prompt treatments and enhance patientoutcomes. This article presents an end-to - end predictive model for the binary classification of CRD inhealthcare, addre ssing the crucial need for early and accurate predictions to enhance patient out comes.”Our news journalists obtained a quote from the research from SRM University, “Th rough hyperparameteroptimization using GridSearchCV, we significantly improve m odel performance. Leveraging a rangeof machine learning (ML) techniques, our ap proach achieves a high predictive accuracy of 99.07% forrandom fo rest, extra trees classifier, logistic regression with L2 penalty, and artificia l neural networks(ANN). Through rigorous evaluation, the logistic regression wi th L2 penalty emerges as the top performer,demonstrating consistent performance . Moreover, integration of Explainable Artificial Intelligence(XAI) techniques, such as Local Interpretable Model- agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP), enhances interpretability and reveals insights into m odel decision-making. Byemphasizing an end-to-end model development process, fr om data collection to deployment, our systemenables real-time predictions and i nformed healthcare decisions.”
Andhra PradeshIndiaAsiaCyborgsEm erging TechnologiesHealth and MedicineKidneyKidney DiseaseKidney Disease s and ConditionsMachine LearningNephrologySRM University
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