Oncology/Hematology

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

15,280 articles
Stay Ahead - Weekly Oncology/Hematology research updates
Subscribe
Browse Categories
Showing 1954-1974 of 15,280 articles
Mixed-Supervised Learning for Cell Classification.

Cell classification based on histopathology images is crucial for tumor recognition and cancer diagn...

Machine learning-based identification of co-expressed genes in prostate cancer and CRPC and construction of prognostic models.

The objective of this study was to employ machine learning to identify shared differentially express...

Advanced image preprocessing and context-aware spatial decomposition for enhanced breast cancer segmentation.

The segmentation of breast cancer diagnosis and medical imaging contains issues such as noise, varia...

Z-SSMNet: Zonal-aware Self-supervised Mesh Network for prostate cancer detection and diagnosis with Bi-parametric MRI.

Bi-parametric magnetic resonance imaging (bpMRI) has become a pivotal modality in the detection and ...

CT-Based Deep Learning Predicts Prognosis in Esophageal Squamous Cell Cancer Patients Receiving Immunotherapy Combined with Chemotherapy.

RATIONALE AND OBJECTIVES: Immunotherapy combined with chemotherapy has improved outcomes for some es...

Towards clinical prediction with transparency: An explainable AI approach to survival modelling in residential aged care.

BACKGROUND AND OBJECTIVE: Scalable, flexible and highly interpretable tools for predicting mortality...

Classification patterns identification of immunogenic cell death-related genes in heart failure based on deep learning.

Heart failure (HF) is a complex and prevalent condition, particularly in the elderly, presenting sym...

CT-based detection of clinically significant portal hypertension predicts post-hepatectomy outcomes in hepatocellular carcinoma.

BACKGROUND: While the CT-based method of detecting clinically significant portal hypertension (CSPH)...

Integrating radiomics and gene expression by mapping on the image with improved DeepInsight for clear cell renal cell carcinoma.

BACKGROUND: Radiomics analysis extracts high-dimensional features from medical images, which are use...

A deep-learning model for predicting tyrosine kinase inhibitor response from histology in gastrointestinal stromal tumor.

Over 90% of gastrointestinal stromal tumors (GISTs) harbor mutations in KIT or PDGFRA that can predi...

Artificial Intelligence in Lymphoma Histopathology: Systematic Review.

BACKGROUND: Artificial intelligence (AI) shows considerable promise in the areas of lymphoma diagnos...

Deep transfer learning based hierarchical CAD system designs for SFM images.

Present work involves rigorous experimentation for classification of mammographic masses by employin...

Predicting cancer survival at different stages: Insights from fair and explainable machine learning approaches.

OBJECTIVES: While prior machine learning (ML) models for cancer survivability prediction often treat...

Integrating single-cell sequencing and machine learning to uncover the role of mitophagy in subtyping and prognosis of esophageal cancer.

Globally, esophageal cancer stands as a prominent contributor to cancer-related fatalities, distingu...

Browse Categories