NA Koohbanani, B Unnikrishnan… - … on Medical Imaging, 2021 - ieeexplore.ieee.org
While high-resolution pathology images lend themselves well to 'data hungry'deep learning algorithms, obtaining exhaustive annotations on these images for learning is a major …
In cancer diagnostics, a considerable amount of data is acquired during routine work-up. Recently, machine learning has been used to build classifiers that are tasked with cancer …
N Al-Azzam, I Shatnawi - Annals of Medicine and Surgery, 2021 - Elsevier
Background Breast cancer disease is the most common cancer in US women and the second cause of cancer death among women. Objectives To compare and evaluate the …
W Wang, R Jiang, N Cui, Q Li, F Yuan… - Frontiers in …, 2022 - frontiersin.org
Various imaging techniques combined with machine learning (ML) models have been used to build computer-aided diagnosis (CAD) systems for breast cancer (BC) detection and …
The trending global pandemic of COVID-19 is the fastest ever impact which caused people worldwide by severe acute respiratory syndrome (SARS)-driven coronavirus. However …
Deep Learning-based Smart Healthcare is getting so much attention due to real-time applicability in everyone life's, and It has obtained more attention with the convergence of …
E Bütün, M Uçan, M Kaya - Biomedical Signal Processing and Control, 2023 - Elsevier
Lymph node metastases are one of the most indicator of some cancer types such as breast, colon and prostate. Breast cancer mostly spreads to lymph nodes in the armpit and it is one …
A Johny, KN Madhusoodanan - … and Mathematical Methods in …, 2021 - Wiley Online Library
Diagnosis of different breast cancer stages using histopathology whole slide images (WSI) is the gold standard in determining the grade of tissue metastasis. Computer‐aided diagnosis …
The annotation of large datasets is often the bottleneck in the successful application of artificial intelligence in computational pathology. For this reason recently Multiple Instance …