Lung Cancer

Hierarchical Machine Learning Uncovers Topological Signatures of Autophagy Regulation by Oral Bacteria in Oral Squamous Cell Carcinoma

Oral squamous cell carcinoma (OSCC) progression has been increasingly linked to dysbiosis of the oral microbiome. We hypothesized that pathogenic versus commensal bacteria differentially rewire host autophagy networks to either promote or inhibit OSCC progression. To test this, we constructed host–bacterium autophagy interactomes from KEGG, STRING, and curated databases, identifying key network hu...

Design of Allosteric Inhibitors for Mutant EGFR by Combined use of Machine Learning and Molecular Dynamics Simulations

The non-small cell lung cancer (NSCLC)-associated Epidermal Growth Factor Receptor (EGFR) mutant L858R/T790M confers resistance to first- and second-generation tyrosine kinase inhibitors (TKIs). Allosteric inhibitors, binding outside the ATP-binding site, have emerged as alternative therapeutic agents. Unlike orthosteric inhibitors, they preferentially stabilize EGFR in an inactive conformation. H...

From Big Data to Small Scales: Machine Learning Enhances Microclimate Model Predictions

1. Microclimates are critical for understanding how organisms interact with their environments, influencing behaviour, physiology, and species distrib...

ROSIE-Enabled Spatial Mapping Reveals Architectural Fragmentation and Immune Reprogramming in Lung Adenocarcinoma Evolution

The progression of lung adenocarcinoma (LUAD) from precancerous lesions to invasive carcinoma entails extensive remodeling of tissue architecture and ...

Microenvironment-Inferred Genotyping: An Exclusionary Classifier for EGFR Amplification When DNA Testing Fails

EGFR amplification occurs in approximately 40-50% of glioblastoma (GBM) cases and is critical for treatment selection [1]. However, GBM tissue samples...

lncAPNet enables the deciphering of lncRNA–mRNA connections in patient transcriptomic data

Long non-coding RNAs (lncRNAs) regulate gene expression through chromatin remodeling, transcriptional control, and post-transcriptional modulation, in...

Subtype-Specific Dependencies and Drug Vulnerabilities Enable Precision Therapeutics in Head and Neck Cancer

Molecular heterogeneity in head and neck squamous cell carcinoma (HNSCC) is well recognized, yet existing subtype frameworks remain largely descriptiv...

Automated imaging-based tumor burden and pre-treatment circulating tumor DNA in HPV-associated oropharynx cancer

Artificial intelligence (AI)-based imaging analysis has applications for the diagnosis of head and neck malignancies, and serum circulating tumor-asso...

Leveraging Longitudinal Patient-Reported Outcomes Trajectories to Predict Survival in Non-Small-Cell Lung Cancer

Despite their potential, patient-reported outcomes (PROs) are often underutilized in clinical decision-making, especially when improvements in PROs do...

Automated Segmentation of Trunk Musculature with a Deep CNN Trained from Sparse Annotations in Radiation Therapy Patients with Metastatic Spine Disease

Given the high prevalence of vertebral fractures post-radiotherapy in patients with metastatic spine disease, accurate and rapid muscle segmentation c...

An autoantibody-based machine learning classifier for the detection of early-stage non-small cell lung cancer

The humoral immune system plays a significant role in the immune response to cancer but is challenging to study at scale. We used programmable phage i...

Prospective Blinded evaluation of Thermalytix, an artificial intelligence-enhanced breast thermal imaging software, correlated with radiologist-interpreted mammograms: Results of an exploratory study in Zambia

While mammography is commonly used for breast cancer detection, its widespread implementation in resource-constrained nations is challenging. Artifici...

Integration of CA attention and KAN algorithm to predict EGFR mutation status in lung cancer

Epidermal Growth Factor Receptor (EGFR) mutations are critical biomarkers for targeted therapies in non-small cell lung cancer (NSCLC). However, conve...

The Rise of the Large Language Models (LLMs): Can They Truly Match Clinical and Data Science Experts in Clinical Trial Data Analysis?

Clinical trials provide evidence of the efficacy and safety of experimental treatment regimens. Analysis of data from these trials is a time-intensive...

Performance of an artificial intelligence foundation model for prostate radiotherapy segmentation

Artificial intelligence (AI) foundation models such as Segment Anything Model 2 (SAM 2) offer potential for semi-automated image segmentation with min...

Integrating etiological insights with machine learning for precision diagnosis of obstructive jaundice: Findings from a high-volume center

Large-scale cohort studies exploring the etiology of obstructive jaundice (OJ) are scarce, with current serum-based diagnostic markers offering subopt...

Pancreatic cancer risk prediction using deep sequential modeling of longitudinal diagnostic and medication records

Pancreatic ductal adenocarcinoma (PDAC) is a rare, aggressive cancer often diagnosed late with low survival rates, due to the lack of population-wide ...

Impact of Iron Deficiency on Clinical Outcomes in Congestive Heart Failure: A Retrospective Analysis of Risk Stratification and Mortality

Iron deficiency frequently coexists with congestive heart failure, thereby increasing morbidity and mortality. Although guidelines typically define ir...

Computational characterization of lymphocyte topology on whole slide images of glomerular diseases

The complexity of distribution of inflammatory cells in the kidney is not well captured by conventional semiquantitative visual assessment. This study...

Large language models for extracting histopathologic diagnoses of colorectal cancer and dysplasia from electronic health records

Accurate data resources are essential for impactful medical research, but available structured datasets are often incomplete or inaccurate. Recent adv...