Demystifying supervised learning in healthcare 4.0: A new reality of transforming diagnostic medicine

S Roy, T Meena, SJ Lim - Diagnostics, 2022 - mdpi.com
The global healthcare sector continues to grow rapidly and is reflected as one of the fastest-
growing sectors in the fourth industrial revolution (4.0). The majority of the healthcare …

Applying deep learning for breast cancer detection in radiology

E Mahoro, MA Akhloufi - Current Oncology, 2022 - mdpi.com
Recent advances in deep learning have enhanced medical imaging research. Breast cancer
is the most prevalent cancer among women, and many applications have been developed to …

On the analyses of medical images using traditional machine learning techniques and convolutional neural networks

S Iqbal, A N. Qureshi, J Li, T Mahmood - Archives of Computational …, 2023 - Springer
Convolutional neural network (CNN) has shown dissuasive accomplishment on different
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …

ResNet-32 and FastAI for diagnoses of ductal carcinoma from 2D tissue slides

SP Praveen, PN Srinivasu, J Shafi, M Wozniak… - Scientific Reports, 2022 - nature.com
Carcinoma is a primary source of morbidity in women globally, with metastatic disease
accounting for most deaths. Its early discovery and diagnosis may significantly increase the …

Breast cancer detection in thermograms using a hybrid of GA and GWO based deep feature selection method

R Pramanik, P Pramanik, R Sarkar - Expert Systems with Applications, 2023 - Elsevier
Breast cancer is one of the most common reasons for the premature death of women
worldwide. However, early detection and diagnosis of the same can save many lives …

Optimized stacking ensemble learning model for breast cancer detection and classification using machine learning

M Kumar, S Singhal, S Shekhar, B Sharma… - Sustainability, 2022 - mdpi.com
Breast cancer is the most frequently encountered medical hazard for women in their forties,
affecting one in every eight women. It is the greatest cause of death worldwide, and early …

Classification of breast cancer from histopathology images using an ensemble of deep multiscale networks

R Karthik, R Menaka, MV Siddharth - Biocybernetics and biomedical …, 2022 - Elsevier
Manual delineation of tumours in breast histopathology images is generally time-consuming
and laborious. Computer-aided detection systems can assist pathologists by detecting …

Attention guided grad-CAM: an improved explainable artificial intelligence model for infrared breast cancer detection

K Raghavan - Multimedia Tools and Applications, 2024 - Springer
Explainable artificial intelligence (XAI) can help build trust between AI models and
healthcare professionals in the context of medical image classification. XAI can help explain …

Breast cancer classification on thermograms using deep CNN and transformers

E Mahoro, MA Akhloufi - Quantitative InfraRed Thermography …, 2024 - Taylor & Francis
Breast thermography is a screening approach for breast cancer detection by measuring the
breast skin temperature. Breast cancer is the most common cancer among women and can …

Breast cancer detection: A comparative review on passive and active thermography

G Jacob, I Jose, S Sujatha - Infrared Physics & Technology, 2023 - Elsevier
Breast cancer is the main cause of death among women due to cancer. Early detection is
crucial in controlling the disease. Thermography is a non-invasive imaging method that uses …