Heart Disease Prediction using SVM

International Journal of Science and Research Archive, Год журнала: 2024, Номер 11(2), С. 412 - 420

Опубликована: Март 18, 2024

Diagnosing and predicting the outcome of cardiovascular disease are essential tasks in medicine that help ensure patients receive accurate classification treatment from cardiologists. The use machine learning healthcare sector has grown due to its ability identify patterns data. By applying techniques classify presence diseases, it's possible decrease rate misdiagnosis. This study aims create a model capable accurately forecasting diseases minimize deaths associated with these conditions. In this paper, two types SVM such as linear polynomial is used. Accuracy, precision, recall F1 score been evaluated for comparing SVM. Polynomial provides better accuracy than

Язык: Английский

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Mechanical characterization of materials using advanced microscopy techniques

World Journal of Advanced Research and Reviews, Год журнала: 2024, Номер 21(3), С. 274 - 283

Опубликована: Март 6, 2024

This review explores the synergistic relationship between advanced microscopy techniques and mechanical engineering, outlining their profound impact on materials science system design. We delve into multifaceted applications of electron microscopy, X-ray diffraction, spectroscopic methods in understanding microstructural dynamics, properties, failure mechanisms integral to engineering. Through a comprehensive synthesis recent research, we emphasize pivotal role these play optimizing material performance, bolstering structural integrity, driving innovation By elucidating intricate details behavior at microscale, contributes informed decision-making selection design processes. Furthermore, address emerging trends prospects, underscoring continued synergy collaboration remains forefront technology, promising ongoing advancements that will shape future landscape innovation.

Язык: Английский

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Pneumonia prediction using deep learning in chest X-ray Images

International Journal of Science and Research Archive, Год журнала: 2024, Номер 12(1), С. 767 - 773

Опубликована: Май 24, 2024

Pneumonia, a potentially fatal lung disease caused by viral or bacterial infection, poses challenges in diagnosis from chest X-ray images due to similarities with other infections. This research aims develop computer-aided system for pneumonia detection children, enhancing diagnostic accuracy. In this paper, five established deep learning models such as VGG-16, VGG-19, ResNet-50, Inception-V3, Xception pre-trained on ImageNet have been used. These applied the dataset optimize performance. provides recall, specificity, accuracy and AUC of 97.43%, 91.02%, 95.06% 94.23%, respectively.

Язык: Английский

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Identifying Edge Cases in Accident Fatalities for Human-Controlled Vehicles via Angle-Based Outlier Detection

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Май 8, 2025

Fatal accidents remain a significant challenge to road safety globally, particularly for human-controlled vehicles (SAE Level 1 and 2). Despite advancements in vehicle technologies, understanding addressing edge cases — scenarios where conventional measures might fail are crucial enhancing standards. This study offers method identification detailed analysis of accident fatalities. Using dataset 39,221 from 2022, the Angle-Based Outlier Detection (ABOD) was employed identify 4,429 cases. The underwent thorough preprocessing feature engineering accurately reflect complexities real-world accidents, including encoding categorical variables, normalizing numerical features, applying ABOD technique pinpoint anomalous data points. effectiveness evaluated using statistical such as ROC AUC scores confusion matrix. highlights critical factors contributing fatalities cases, revealing previously underappreciated aspects safety. implications improving discussed detail. research lays groundwork future studies on advanced systems automated utilizing outlier detection generate actionable insights

Язык: Английский

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Encouraging Safety 4.0 to enhance industrial culture: An extensive study of its technologies, roles, and challenges

Green Technologies and Sustainability, Год журнала: 2024, Номер unknown, С. 100158 - 100158

Опубликована: Дек. 1, 2024

Язык: Английский

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