Oncology/Hematology

Lung Cancer

Latest AI and machine learning research in lung cancer for healthcare professionals.

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Showing 1-21 of 8,029 articles
Deep learning and radiomics fusion for predicting the invasiveness of lung adenocarcinoma within ground glass nodules.

Microinvasive adenocarcinoma (MIA) and invasive adenocarcinoma (IAC) require distinct treatment stra...

Identifying ferroptosis-related genes in lung adenocarcinoma using random walk with restart in the PPI network.

Lung adenocarcinoma (LUAD), the most common non-small cell lung cancer subtype, often presents with ...

Can Machine Learning Predict Metastatic Sites in Pancreatic Ductal Adenocarcinoma? A Radiomic Analysis.

Pancreatic ductal adenocarcinoma (PDAC) exhibits high metastatic potential, with distinct prognoses ...

Association between exposure to air pollution and kidney function decline.

BACKGROUND AND HYPOTHESIS: Chronic kidney disease is a major global health concern, with air polluti...

Advances in renal cancer: diagnosis, treatment, and emerging technologies.

This review provides a comprehensive overview of current practices and recent advancements in the di...

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...

Machine learning-driven prognostic and diagnostic models for lung adenocarcinoma using intratumor heterogeneity and multi-omics data.

Intratumor heterogeneity (ITH) significantly impacts cancer prognosis and treatment response. Focusi...

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...

A deep learning model for predicting radiation-induced xerostomia in patients with head and neck cancer based on multi-channel fusion.

OBJECTIVES: Radiation-induced xerostomia is a common sequela in patients who undergo head and neck r...

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...

CRISPR-GPT for agentic automation of gene-editing experiments.

Performing effective gene-editing experiments requires a deep understanding of both the CRISPR techn...

Identification of DNA damage response and crotonylation-related biomarkers for lung adenocarcinoma via machine learning and WGCNA.

DNA damage response (DDR) and crotonylation occur frequently in lung adenocarcinoma (LUAD), but thei...

Comprehensive analysis of cholesterol metabolism-related genes in prostate cancer: integrated analysis of single-cell and bulk RNA sequencing.

BACKGROUND: Cholesterol metabolism plays a significant role in cancer progression, including prostat...

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