Oncology/Hematology

Other Cancers

Latest AI and machine learning research in other cancers for healthcare professionals.

8,290 articles
Stay Ahead - Weekly Other Cancers research updates
Subscribe
Browse Specialties
Showing 64-84 of 8,290 articles
Graph theoretic and machine learning approaches in molecular property prediction of bladder cancer therapeutics.

This work introduces a hybrid computational approach in which degree-based topological descriptors a...

Integrated transcriptomic and functional modeling reveals AKT and mTOR synergy in colorectal cancer.

Colorectal cancer (CRC) treatment remains challenging due to genetic heterogeneity and resistance me...

Machine learning-based design, screening, and activity validation of topoisomerase I inhibitors.

Topoisomerase I (TOP I) plays a vital role in maintaining genomic stability and regulating cellular ...

Integrative network pharmacology and multi-omics reveal anisodamine hydrobromide's multi-target mechanisms in sepsis.

Sepsis, marked by hyperinflammation and subsequent immunosuppression, lacks effective phase-specific...

Mitochondrial Pathway Signature (MitoPS) predicts immunotherapy response and reveals NDUFB10 as a key immune regulator in lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer. Alt...

Pan-cancer Analyses Refine the Single-Cell Portrait of Tumor-Infiltrating Dendritic Cells.

Dendritic cells (DCs) are pivotal orchestrators of anti-tumor immunity. DC-based anti-tumor treatmen...

GPSai: A Clinically Validated AI Tool for Tissue of Origin Prediction During Routine Tumor Profiling.

A subset of cancers presents with unclear or potentially incorrect primary histopathologic diagnoses...

Longitudinal single-cell RNA model aids prediction of EGFR-TKI resistance.

Resistance is inevitable and a major challenge in treating Lung adenocarcinoma (LUAD) patients with ...

Deep learning-based real-time detection of head and neck tumors during radiation therapy.

Clinical drivers for real-time head and neck (H&N) tumor tracking during radiation therapy (RT) are ...

Radiation enteritis associated with temporal sequencing of total neoadjuvant therapy in locally advanced rectal cancer: a preliminary study.

BACKGROUND: This study aimed to develop and validate a multi-temporal magnetic resonance imaging (MR...

Gut microbiome in gastrointestinal neoplasms: from mechanisms to precision therapeutic strategies.

BACKGROUND: The incidence of Gastrointestinal Neoplasms (GI neoplasms) continues to increase globall...

HLAIIPred: cross-attention mechanism for modeling the interaction of HLA class II molecules with peptides.

We introduce HLAIIPred, a deep learning model to predict peptides presented by class II human leukoc...

Predicting ROS1 and ALK fusions in NSCLC from H&E slides with a two-step vision transformer approach.

Non-small cell lung cancer (NSCLC) is one of the deadliest and most prevalent cancers worldwide, wit...

Histopathological-based brain tumor grading using 2D-3D multi-modal CNN-transformer combined with stacking classifiers.

Reliability in diagnosing and treating brain tumors depends on the accurate grading of histopatholog...

High-Resolution Ultrasound Data for AI-Based Segmentation in Mouse Brain Tumor.

Glioblastoma multiforme (GBM) is the most aggressive type of brain cancer, making effective treatmen...

"Screening" for End of Life Using Artificial Intelligence: A Qualitative Study of Palliative Care Team Members' Perspectives on Ethical Use.

Artificial intelligence (AI) tools for health care applications are rapidly emerging. Some AI-based...

Intraductal Papillary Mucinous Neoplasm and Pancreatic Cancer: Opportunity Knocks Twice.

Pancreatic cystic lesions are widely recognized as harbingers of pancreatic cancer. Intraductal papi...

Deep learning neural network of adenocarcinoma detection in effusion cytology.

OBJECTIVE: Cytologic examination, which confirms the presence or absence of malignant cells, detects...

An interpretable machine learning model for preoperative prediction of renal mass malignancy.

OBJECTIVE: To develop and validate a predictive model for distinguishing benign and malignant renal ...

Browse Specialties