Stacking ensemble based hyperparameters to diagnosing of heart disease: Future works

Results in Engineering, Journal Year: 2024, Volume and Issue: 21, P. 101894 - 101894

Published: Feb. 12, 2024

Heart disease is one of the most recurrent and worrying health problems today, due to its multiple complications, including: stroke, cardiac arrest, retinopathy, etc. Propose a method 4 Stacking models based on hyperparameters diagnose heart disease. In addition, web interface was developed with best model proposed in this study. First, dataset used from Disease Cleveland ICU, which 918 patient records 12 attributes. Therefore, paper composed following stages: Cleaning Pre-processing; Describe data; Training testing Cross validation; Calibration models; modelling evaluation, also compare different techniques predict using ensemble taking into account performance evaluation parameters. 1 (Logistic regression) oversampling AdaBoost-SVM hyperparameter test obtained higher Accuracy (88.24%), ROC Curve (92.00%), while too reached better Precision (88.54%), but algorithm achieved high value Sensitivity (88.14%) F1-Score (88.19%). Implementing stacking hyperparameters, it helps make an early diagnosis greater precision, decrease quantity deceases caused by it. combined method, improvement prediction observed, surpassing independent algorithms used.

Language: Английский

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Performance evaluation of Machine Learning models to predict heart attack

Machine Graphics and Vision, Journal Year: 2023, Volume and Issue: 32(1)

Published: Aug. 14, 2023

Coronary Artery Disease is the type of cardiovascular disease (CVD) that happens when blood vessels which stream toward heart, either become tapered or blocked. Of this, heart incapable to push sufficient encounter its requirements. This would lead angina (chest pain). CVDs are leading cause mortality worldwide. According WHO, in year 2019 17.9 million people deceased from CVD. Machine Learning a artificial intelligence uses algorithms help analyse large datasets more efficiently. It can be used medical research process amounts data quickly, such as patient records images. By using techniques and methods, scientists automate analysis complex gain deeper insights into data. technology helps with gathering understanding patterns. Recently, researchers healthcare industry have been assist diagnosing heart-related diseases. means professionals involved diagnosis use them figure out what wrong provide appropriate treatment. paper evaluates different machine learning models performances. The Supervised commonly training done labelled data, belonging particular classification. Such classification methods like Random Forest, Decision Tree, K-Nearest Neighbour, XGBoost algorithm, Naive Bayes, Support Vector will assess by Learning.

Language: Английский

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Disease Prediction Based on Symptoms and Drug Recommendation

2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), Journal Year: 2024, Volume and Issue: unknown, P. 1 - 6

Published: March 14, 2024

Within the sphere of healthcare, widespread employment large datasets has infiltrated each element field, starting from groundbreaking scientific inquiry right through to optimizing patient interactions and therapeutic results. With a myriad diverse ailments challenging healthcare systems worldwide, integration Machine Learning Big Data technologies emerged as novel approach disease prediction diagnosis. This research embarks on transformative journey, investigating application machine learning algorithms forecast diseases based presenting symptoms provide drug recommendation. Through implementation Naive Bayes, Decision Trees, Random Forests, Logistic Regression, this study explores path more accurate data-driven solutions.

Language: Английский

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Enhancing Heart Disease Prediction: A Comparative Analysis of Machine Learning Models Using Extended Health Parameter Sets

Lecture notes in networks and systems, Journal Year: 2024, Volume and Issue: unknown, P. 599 - 613

Published: Jan. 1, 2024

Language: Английский

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Heart Disease Prediction Model Using Machine Learning Techniques

Communications in computer and information science, Journal Year: 2024, Volume and Issue: unknown, P. 290 - 301

Published: Sept. 25, 2024

Language: Английский

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Comparative analysis of machine learning and ensemble approaches for hepatitis B prediction using data mining with synthetic minority oversampling technique

Health and Technology, Journal Year: 2023, Volume and Issue: unknown

Published: Nov. 29, 2023

Language: Английский

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