Towards label-efficient automatic diagnosis and analysis: a comprehensive survey of advanced deep learning-based weakly-supervised, semi-supervised and self …
Histopathological images contain abundant phenotypic information and pathological
patterns, which are the gold standards for disease diagnosis and essential for the prediction …
patterns, which are the gold standards for disease diagnosis and essential for the prediction …
Self-path: Self-supervision for classification of pathology images with limited annotations
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 …
algorithms, obtaining exhaustive annotations on these images for learning is a major …
Semi-supervised learning in cancer diagnostics
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 …
Recently, machine learning has been used to build classifiers that are tasked with cancer …
[HTML][HTML] Comparing supervised and semi-supervised machine learning models on diagnosing breast 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 …
second cause of cancer death among women. Objectives To compare and evaluate the …
Semi-supervised vision transformer with adaptive token sampling for breast cancer classification
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 …
to build computer-aided diagnosis (CAD) systems for breast cancer (BC) detection and …
Covidpen: A novel covid-19 detection model using chest x-rays and ct scans
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 …
worldwide by severe acute respiratory syndrome (SARS)-driven coronavirus. However …
Deep learning-based smart IoT health system for blindness detection using retina images
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 …
applicability in everyone life's, and It has obtained more attention with the convergence of …
Automatic detection of cancer metastasis in lymph node using deep learning
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 …
colon and prostate. Breast cancer mostly spreads to lymph nodes in the armpit and it is one …
Dynamic learning rate in deep CNN model for metastasis detection and classification of histopathology images
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 gold standard in determining the grade of tissue metastasis. Computer‐aided diagnosis …
Efficient cancer classification by coupling semi supervised and multiple instance learning
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 …
artificial intelligence in computational pathology. For this reason recently Multiple Instance …