Heart Disease Prediction using SVM

International Journal of Science and Research Archive, Journal Year: 2024, Volume and Issue: 11(2), P. 412 - 420

Published: March 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

Language: Английский

---

Pneumonia prediction using deep learning in chest X-ray Images

International Journal of Science and Research Archive, Journal Year: 2024, Volume and Issue: 12(1), P. 767 - 773

Published: May 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.

Language: Английский

---

Mechanical characterization of materials using advanced microscopy techniques

World Journal of Advanced Research and Reviews, Journal Year: 2024, Volume and Issue: 21(3), P. 274 - 283

Published: March 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.

Language: Английский

---

Empowering blockchain with SmartNIC: Enhancing performance, security, and scalability

World Journal of Advanced Research and Reviews, Journal Year: 2024, Volume and Issue: 22(1), P. 151 - 162

Published: April 7, 2024

This paper introduces BlockNIC, an innovative blockchain infrastructure designed to operate exclusively on SmartNICs. Unlike traditional implementations, BlockNIC leverages the unique capabilities of SmartNICs execute relatively simple computations directly network path, eliminating need for additional hardware and reducing reliance host CPUs. By harnessing idle resources within network, significantly reduces energy consumption requirements, addressing environmental concerns associated with conventional architectures. Through comprehensive performance comparisons between bare-metal servers, this study demonstrates promising potential in achieving scalability, security, sustainability networks. The findings highlight BlockNIC's ability enhance overall reliability while minimizing resource limitations, thereby unlocking new possibilities various applications use cases previously hindered by constraints. emergence aligns global agenda, offering a timely solution challenges posed technologies. promoting adoption SmartNIC-based infrastructures, research contributes greener more secure digital future. It emphasizes importance exploring approaches address impact technological innovations, urging researchers, industry professionals, policymakers recognize transformative solutions advancing efficiency ecosystems.

Language: Английский

---

Novel Ensemble Learning Algorithm for Early Detection of Lower Back Pain Using Spinal Anomalies

Mathematics, Journal Year: 2024, Volume and Issue: 12(13), P. 1955 - 1955

Published: June 24, 2024

Lower back pain (LBP) is a musculoskeletal condition that affects millions of people worldwide and significantly limits their mobility daily activities. Appropriate ergonomics exercise are crucial preventive measures play vital role in managing reducing the risk LBP. Individuals with LBP often exhibit spinal anomalies, which can serve as valuable indicators for early diagnosis. We propose an advanced machine learning methodology detection incorporates data balancing bootstrapping techniques. Leveraging features associated our method offers promising approach Our study utilizes standard dataset comprising 310 patient records, including anomaly features. ensemble called random forest gradient boosting XGBoost Ensemble (RGXE), integrates combined power forest, boosting, methods detection. Experimental results demonstrate proposed method, RGXE Voting, outperforms state-of-the-art methods, achieving high accuracy 0.99. fine-tuned each validated its performance using k-fold cross-validation addition to determining computational complexity methods. This innovative research holds significant potential revolutionize LBP, thereby improving quality life.

Language: Английский

---

Hepatitis C prediction using SVM, logistic regression and decision tree

World Journal of Advanced Research and Reviews, Journal Year: 2024, Volume and Issue: 22(2), P. 926 - 936

Published: May 16, 2024

Hepatitis C is an infection of the liver brought on by HCV virus. In this condition, early diagnosis challenging because delayed onset symptoms. Predicting well enough can spare patients from permeant damage. The primary goal work to use several machine learning methods forecast disease based widely available and reasonably priced blood test data in order diagnose treat on. Three techniques support vector (SVM), logistic regression, decision tree, has been applied one dataset work. To find a suitable approach for illness prediction, confusion matrix, precision, recall, F1 score, accuracy, receiver operating characteristics (ROC), performances different strategies have assessed. SVM model's overall accuracy 0.92, highest among three models.

Language: Английский

---

Enhanced breast cancer detection and classification via CAMR-Gabor filters and LSTM: A deep Learning-Based method

Egyptian Informatics Journal, Journal Year: 2025, Volume and Issue: 29, P. 100602 - 100602

Published: Jan. 8, 2025

Language: Английский

---

Improving Breast Cancer Diagnosis through Advanced Image Analysis and Neural Network Classifications

Procedia Computer Science, Journal Year: 2025, Volume and Issue: 252, P. 73 - 80

Published: Jan. 1, 2025

Language: Английский

---

Investigating the effectiveness of a mobile wind turbine generating electricity from vehicle air movement

World Journal of Advanced Research and Reviews, Journal Year: 2024, Volume and Issue: 22(1), P. 210 - 218

Published: April 9, 2024

This study presents an evaluation of the effectiveness a portable wind generator designed to harness flow generated by moving vehicles for electricity production. With growing emphasis on renewable energy sources and need sustainable power solutions, innovative approaches such as utilizing vehicle-induced currents have gained attention. The under examination is engineered capture airflow from passing convert it into electrical energy. Through combination field experiments theoretical analysis, performance efficiency device were assessed various environmental traffic conditions. Factors speed, direction, vehicle velocity considered in process. results indicate promising potential supplementary source, particularly environments with high vehicular traffic. However, challenges variability patterns optimal positioning remain areas further investigation refinement. Overall, this contributes understanding unconventional resources provides insights practical implementation mobile technology generation.

Language: Английский

---

Technological trends in 5G networks for IoT-enabled smart healthcare: A review

International Journal of Science and Research Archive, Journal Year: 2024, Volume and Issue: 12(2), P. 1399 - 1410

Published: July 30, 2024

Smart healthcare is in the process of quick evolution from traditional focused approach towards specialist and hospital to a patient-centric model. The following technological advancements have boosted this revolution vertical. Presently, 4G as well other communication standards like WLAN are applied offer smart services solutions. considers apply for advancement further future. It reason that industry expands, several applications anticipated generate huge volume data various forms sizes. Thus, enormous varying requires special end-to-end delay, bandwidth, latency factors. it becomes highly challenging current technologies effectively support complex sensitive health care these 5G networks being planned implemented address multifaceted requirements IoT. assisted consist IoT devices which need better network performance extended cellular connections. There issues with existing connectivity solutions namely how many can be connected, achieving global standardization, optimizing low power budgets, fit into given area secure communication. This paper aims provide an elaborate review by technology.

Language: Английский

---