Oncology/Hematology

Latest AI and machine learning research in oncology/hematology for healthcare professionals.

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Transformer-based unsupervised contrastive learning for histopathological image classification.

A large-scale and well-annotated dataset is a key factor for the success of deep learning in medical...

A Novel Deep Learning Model to Distinguish Malignant Versus Benign Solid Lung Nodules.

BACKGROUND In this study we aimed to establish a new transfer learning model based on noncontrast an...

SCDNet: A Deep Learning-Based Framework for the Multiclassification of Skin Cancer Using Dermoscopy Images.

Skin cancer is a deadly disease, and its early diagnosis enhances the chances of survival. Deep lear...

The Use of Deep Learning-Based Computer Diagnostic Algorithm for Detection of Lymph Node Metastases of Gastric Adenocarcinoma.

The diversifying modalities of treatment for gastric cancer raise urgent demands for the rapid and ...

Automated histological classification for digital pathology images of colonoscopy specimen via deep learning.

Colonoscopy is an effective tool to detect colorectal lesions and needs the support of pathological ...

Classification and Detection of Mesothelioma Cancer Using Feature Selection-Enabled Machine Learning Technique.

Cancer of the mesothelium, sometimes referred to as malignant mesothelioma (MM), is an extremely unc...

An Efficient Multi-Scale Convolutional Neural Network Based Multi-Class Brain MRI Classification for SaMD.

A brain tumor is the growth of abnormal cells in certain brain tissues with a high mortality rate; t...

Detection of Pancreatic Cancer in CT Scan Images Using PSO SVM and Image Processing.

A diagnosis of pancreatic cancer is one of the worst cancers that may be received anywhere in the wo...

Comparison of Two-Port and Three-Port Approaches in Robotic Lobectomy for Non-Small Cell Lung Cancer.

BACKGROUND: Robot-assisted lobectomy has been used to treat non-small cell lung cancer and usually u...

Clinical Validation of a Deep-Learning Segmentation Software in Head and Neck: An Early Analysis in a Developing Radiation Oncology Center.

BACKGROUND: Organs at risk (OARs) delineation is a crucial step of radiotherapy (RT) treatment plann...

BO-ALLCNN: Bayesian-Based Optimized CNN for Acute Lymphoblastic Leukemia Detection in Microscopic Blood Smear Images.

Acute lymphoblastic leukemia (ALL) is a deadly cancer characterized by aberrant accumulation of imma...

Gene Identification and Potential Drug Therapy for Drug-Resistant Melanoma with Bioinformatics and Deep Learning Technology.

BACKGROUND: Melanomas are skin malignant tumors that arise from melanocytes which are primarily trea...

Development and validation of a meta-learning-based multi-modal deep learning algorithm for detection of peritoneal metastasis.

PURPOSE: The existing medical imaging tools have a detection accuracy of 97% for peritoneal metastas...

Deep learning for brain metastasis detection and segmentation in longitudinal MRI data.

PURPOSE: Brain metastases (BM) occur frequently in patients with metastatic cancer. Early and accura...

A deep image-to-image network organ segmentation algorithm for radiation treatment planning: principles and evaluation.

BACKGROUND: We describe and evaluate a deep network algorithm which automatically contours organs at...

Accurate somatic variant detection using weakly supervised deep learning.

Identification of somatic mutations in tumor samples is commonly based on statistical methods in com...

ALNett: A cluster layer deep convolutional neural network for acute lymphoblastic leukemia classification.

Acute Lymphoblastic Leukemia (ALL) is cancer in which bone marrow overproduces undeveloped lymphocyt...

Marker-controlled watershed with deep edge emphasis and optimized H-minima transform for automatic segmentation of densely cultivated 3D cell nuclei.

BACKGROUND: The segmentation of 3D cell nuclei is essential in many tasks, such as targeted molecula...

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