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Computational intelligence in cancer diagnostics: A contemporary review of smart phone apps, current problems, and future research potentials
Cancer is a dangerous and sometimes life-threatening disease that can have several
negative consequences for the body, is a leading cause of mortality, and is becoming …
negative consequences for the body, is a leading cause of mortality, and is becoming …
Deep learning empowered breast cancer diagnosis: Advancements in detection and classification
Recent advancements in AI, driven by big data technologies, have reshaped various
industries, with a strong focus on data-driven approaches. This has resulted in remarkable …
industries, with a strong focus on data-driven approaches. This has resulted in remarkable …
IIMFCBM: Intelligent integrated model for feature extraction and classification of brain tumors using MRI clinical imaging data in IoT-healthcare
Accurate classification of brain tumors is vital for detecting brain cancer in the Medical
Internet of Things. Detecting brain cancer at its early stages is a tremendous medical …
Internet of Things. Detecting brain cancer at its early stages is a tremendous medical …
Diagnostic approach for accurate diagnosis of COVID-19 employing deep learning and transfer learning techniques through chest X-ray images clinical data in E …
COVID-19 is a transferable disease that is also a leading cause of death for a large number
of people worldwide. This disease, caused by SARS-CoV-2, spreads very rapidly and …
of people worldwide. This disease, caused by SARS-CoV-2, spreads very rapidly and …
[HTML][HTML] Bayesian depth-wise convolutional neural network design for brain tumor MRI classification
In recent years, deep learning has been applied to many medical imaging fields, including
medical image processing, bioinformatics, medical image classification, segmentation, and …
medical image processing, bioinformatics, medical image classification, segmentation, and …
Predicting breast cancer risk from histopathology images using hybrid deep learning classifier
G Sajiv, G Ramkumar, S Shanthi… - Medical Engineering & …, 2024 - Elsevier
Millions of people per year pass away from breast cancer (BC), which is a fatal illness. To
deal with this issue more effectively, diagnoses can be made more scalable and less prone …
deal with this issue more effectively, diagnoses can be made more scalable and less prone …
Towards Early Breast Cancer Detection: A Deep Learning Approach
A Bekkouche, M Merzoug, M Hadjila… - Engineering, Technology & …, 2024 - etasr.com
Early detection of breast cancer is crucial for patients' recovery chances to be improved.
Artificial intelligence techniques, and more particularly Deep Learning (DL), may contribute …
Artificial intelligence techniques, and more particularly Deep Learning (DL), may contribute …
Enhancing clinical support for breast cancer with deep learning models using synthetic correlated diffusion imaging
Breast cancer is the second most common type of cancer in women in Canada and the
United States, representing over 25% of all new female cancer cases. As such, there has …
United States, representing over 25% of all new female cancer cases. As such, there has …
[PDF][PDF] Cancer-net bca: Breast cancer pathologic complete response prediction using volumetric deep radiomic features from synthetic correlated diffusion imaging
Breast cancer is the second most common type of cancer in women in Canada and the
United States, representing over 25% of all new female cancer cases. Neoadjuvant …
United States, representing over 25% of all new female cancer cases. Neoadjuvant …
[PDF][PDF] Bayesian depthwise convolutional neural network design for brain tumor MRI classification. Diagnostics. 2022; 12: 1657
In recent years, deep learning has been applied to many medical imaging fields, including
medical image processing, bioinformatics, medical image classification, segmentation, and …
medical image processing, bioinformatics, medical image classification, segmentation, and …