Lung Cancer

Exploratory identification of COL1A1 as a potential gene linking endocrine-disrupting chemicals and lung adenocarcinoma: a bioinformatics and machine learning analysis.

BACKGROUND: Endocrine-disrupting chemicals (EDCs) are common environmental pollutants that affect hu...

CanSig Benchmarks Methods for Reproducible Cancer Cell State Discovery from Single-Cell Transcriptomic Data.

UNLABELLED: Single-cell RNA sequencing facilitates the discovery of gene expression signatures that ...

Clinical validation of perfusion imaging with pulmonary function test data using Voronoi-based discretization.

Accurate lung function assessment is essential for diagnosing and managing diseases like COPD, pulmo...

Emerging Roles of Multiparametric Biodosimetry and Artificial Intelligence in Advancing Radiation Dose Assessment for Triage.

Biodosimetry plays a crucial role in radiation emergency preparedness and response by enabling effic...

A Flexible Hybrid Quantum-classical Training Framework of Organ-at-Risk and Tumor Segmentation Models for Radiation Therapy Planning.

Deep learning-based Organ-at-Risk (OAR) and tumor segmentation is vital for radiation therapy planni...

A machine learning-based pharmacokinetics predictor (EGFR-PROPK) for EGFR-targeting PROTACs.

PROteolysis TArgeting Chimeras (PROTACs) are bifunctional molecules that offer a novel approach to t...

Utilisation of intramuscular and intermuscular fat to develop a new skeletal muscle grading score which can predict treatment outcomes for locally advanced rectal cancer.

BACKGROUND: Sarcopenia has been widely studied in rectal cancer with increasing evidence to suggest ...

Toward Timely Diagnosis of Pancreatic Cancer: Revolutionizing Early Detection Through Genomics, Artificial Intelligence, and Noninvasive Biomarkers.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) remains one of the most aggressive cancers, typi...

Peripheral immune landscape in pancreatic ductal adenocarcinoma reveals expansion of effector states with disease progression.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy often diagnosed late due to th...

Integrative bioinformatics identifies NSCLC biomarkers associated with LPS metabolism and circadian disruption.

PURPOSE: Non-small cell lung carcinoma (NSCLC) is a leading cause of cancer-related mortality worldw...

Feasibility of BMI-based sub-milliSievert low-dose CT in individualized detection of lung nodules.

OBJECTIVES: To evaluate the performance of a body mass index (BMI)-based sub-milliSievert low-dose C...

Predicting neoadjuvant immunotherapy efficacy with machine learning models in non-small cell lung cancer: A systematic review and meta analysis.

BACKGROUND: The response of resectable non-small cell lung cancer (NSCLC) to neoadjuvant immunothera...

Integrative transcriptomic and machine learning framework reveals candidate genes and potential mechanisms of aflatoxin B1 exposure in breast cancer.

Aflatoxin B1 (AFB1), a known mycotoxin and environmental hazard, has been linked to breast cancer, y...

Pathomic model to predict the expression of UQCRH and overall survival of lung adenocarcinoma patients.

Interpreting cancer genetics through a two-step "evolutionary cascade hypothesis": bridging neutral and selective perspectives.

BACKGROUND: DNA mutations are the fundamental engines of cancer, driving its initiation and progress...

A deep learning and morphometric hybrid model for automated quantification of kidney interstitial fibrosis in trichrome-stained whole-slide image.

BACKGROUND: Interstitial fibrosis (IF) is the strongest predictor of chronic kidney disease progress...

Prediction model for ctDNA detectability in liquid comprehensive genomic profiling of advanced pancreatic cancer based on Japanese real-world data.

BACKGROUND: Circulating tumor DNA (ctDNA) is sometimes undetectable in liquid comprehensive genomic ...

[The Digital Lab: Practical digital workflow and integration of AI for routine in pathology, through the example of prostate cancer].

Digital pathology is a major technological revolution for pathology. It modernizes routine practices...

Reinforcement learning-guided segment anything model for MRI prostate and dominant intraprostatic lesions auto-segmentation.

Objective. Accurate segmentation of the prostate and dominant intraprostatic lesions (DILs) on magne...

Ancestry-Associated Performance Variability of Open-Source AI Models for EGFR Prediction in Lung Cancer.

IMPORTANCE: Artificial intelligence (AI) models are emerging as rapid, low-cost tools for predicting...

Toward genomic personalization of breast cancer radiotherapy: foundations, challenges, and a roadmap for clinical integration.

Personalizing radiotherapy dose in breast cancer remains a major unmet need, as current treatment pa...