Oncology/Hematology

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

15,647 articles
Stay Ahead - Weekly Oncology/Hematology research updates
Subscribe
Browse Categories
Showing 7603-7623 of 15,647 articles
An optimal brain tumor detection by convolutional neural network and Enhanced Sparrow Search Algorithm.

Precise and timely detection of brain tumor area has a very high effect on the selection of medical ...

Histopathology classification and localization of colorectal cancer using global labels by weakly supervised deep learning.

Colorectal cancer (CRC) is the second leading cause of cancer-related mortality worldwide. In coping...

Deep learning based prediction of prognosis in nonmetastatic clear cell renal cell carcinoma.

Survival analyses for malignancies, including renal cell carcinoma (RCC), have primarily been conduc...

Current cancer driver variant predictors learn to recognize driver genes instead of functional variants.

BACKGROUND: Identifying variants that drive tumor progression (driver variants) and distinguishing t...

Automatic detection and segmentation of multiple brain metastases on magnetic resonance image using asymmetric UNet architecture.

Detection of brain metastases is a paramount task in cancer management due both to the number of hig...

DaNet: dose-aware network embedded with dose-level estimation for low-dose CT imaging.

Many deep learning (DL)-based image restoration methods for low-dose CT (LDCT) problems directly emp...

Deep Multi-Magnification Networks for multi-class breast cancer image segmentation.

Pathologic analysis of surgical excision specimens for breast carcinoma is important to evaluate the...

Research on Early Warning Mechanism and Model of Liver Cancer Rehabilitation Based on CS-SVM.

Since the 20 century, cancer has become one of the main diseases threatening human health. Liver can...

A Machine Learning Approach Yields a Multiparameter Prognostic Marker in Liver Cancer.

A number of staging systems have been developed to predict clinical outcomes in hepatocellular carci...

Robust breast cancer detection in mammography and digital breast tomosynthesis using an annotation-efficient deep learning approach.

Breast cancer remains a global challenge, causing over 600,000 deaths in 2018 (ref. ). To achieve ea...

GVES: machine learning model for identification of prognostic genes with a small dataset.

Machine learning may be a powerful approach to more accurate identification of genes that may serve ...

Preserving image texture while reducing radiation dose with a deep learning image reconstruction algorithm in chest CT: A phantom study.

PURPOSE: To assess whether a deep learning image reconstruction algorithm (TrueFidelity) can preserv...

Integration of human cell lines gene expression and chemical properties of drugs for Drug Induced Liver Injury prediction.

MOTIVATION: Drug-induced liver injury (DILI) is one of the primary problems in drug development. Ear...

Convolutional autoencoder based model HistoCAE for segmentation of viable tumor regions in liver whole-slide images.

Liver cancer is one of the leading causes of cancer deaths in Asia and Africa. It is caused by the H...

Breath biopsy of breast cancer using sensor array signals and machine learning analysis.

Breast cancer causes metabolic alteration, and volatile metabolites in the breath of patients may be...

Automated segmentation of endometrial cancer on MR images using deep learning.

Preoperative MR imaging in endometrial cancer patients provides valuable information on local tumor ...

A deep learning approach for staging embryonic tissue isolates with small data.

Machine learning approaches are becoming increasingly widespread and are now present in most areas o...

Comparison of different machine learning approaches to predict dental age using Demirjian's staging approach.

CONTEXT: Dental age, one of the indicators of biological age, is inferred by radiological methods. T...

Lung cancer histology classification from CT images based on radiomics and deep learning models.

Adenocarcinoma (AC) and squamous cell carcinoma (SCC) are frequent reported cases of non-small cell ...

Browse Categories