2022 7th International Conference on Communication and Electronics Systems (ICCES), Journal Year: 2024, Volume and Issue: unknown, P. 1169 - 1174
Published: Dec. 16, 2024
Language: Английский
World Journal of Advanced Research and Reviews, Journal Year: 2024, Volume and Issue: 21(2), P. 1985 - 1994
Published: Feb. 28, 2024
Breast cancer continues to be one of the foremost illnesses that results in deaths numerous women each year. Among female population, approximately 8% are diagnosed with (BC), following Lung Cancer. The alarming rise fatality rates can attributed breast being second leading cause. manifests through genetic transformations, persistent pain, alterations size, color (redness), and texture breast's skin. Pathologists rely on classification identify a specific targeted prognosis, achieved binary (normal/abnormal). Artificial intelligence (AI) has been employed diagnose tumors swiftly accurately at an early stage. This study employs Extreme Gradient Boosting (XGBoost) machine learning technique for detection analysis cancer. XGBoost provides accuracy 94.74% recall 95.24% Wisconsin (diagnostic) dataset.
Language: Английский
Citations
28
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
Citations
16
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
Citations
9
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
Citations
8
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
Citations
8
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
Citations
4
Lecture notes in computer science, Journal Year: 2025, Volume and Issue: unknown, P. 165 - 182
Published: Jan. 1, 2025
Language: Английский
Citations
0
Intelligent Data Analysis, Journal Year: 2025, Volume and Issue: unknown
Published: March 11, 2025
Skin cancer, particularly melanoma, arises from DNA damage that leads to abnormal cell growth in the epidermis. Early detection is crucial as melanoma can spread rapidly, but it highly curable if identified promptly. Detecting and diagnosing early are essential reduce mortality rates associated with this type of cancer. In literature, various ensemble techniques have been proposed improve performance. This paper introduces a deep learning based method aimed at enhancing accuracy skin cancer detection. Additionally, presents thorough performance evaluation five techniques. Initially, dataset underwent pre-processing, involving removal artifacts through hair removal, achieving balance distribution images for each class image augmentation Then, architecture 16 pre-trained models was modified by adding additional layers their The achieved highest were selected ensembling. Since VGG16, MobileNetV2, DenseNet169 accuracy, they chosen Five techniques, namely, weighted average, voting, bagging, boosting, stacking, applied architectures fine-tuned such classify images. experiments performed on combined HAM10000 ISIC2019, which contains seven lesion classes. results demonstrate average model achieves overall 81.99% classification 89.85%. positive outcomes affirm employing adjusted enhances performance, thereby demonstrating potential utility
Language: Английский
Citations
0
Alexandria Engineering Journal, Journal Year: 2025, Volume and Issue: 125, P. 566 - 574
Published: April 23, 2025
Language: Английский
Citations
0
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
Citations
3