Lung Cancer

Application of improved glomerular filtration rate estimation by a neural network model in patients with neurogenic lower urinary tract dysfunction.

BACKGROUND: Previous studies have indicated that creatinine (Cr)-based glomerular filtration rate (G...

Improving Prediction of Survival and Progression in Metastatic Non-Small Cell Lung Cancer After Immunotherapy Through Machine Learning of Circulating Tumor DNA.

PURPOSE: To use modern machine learning approaches to enhance and automate the feature extraction fr...

Exploring Negated Entites for Named Entity Recognition in Italian Lung Cancer Clinical Reports.

This paper explores the potential of leveraging electronic health records (EHRs) for personalized he...

ctGAN: combined transformation of gene expression and survival data with generative adversarial network.

Recent studies have extensively used deep learning algorithms to analyze gene expression to predict ...

Machine Learning Links T-cell Function and Spatial Localization to Neoadjuvant Immunotherapy and Clinical Outcome in Pancreatic Cancer.

Tumor molecular data sets are becoming increasingly complex, making it nearly impossible for humans ...

Artificial Intelligence Enhances NSCLC Care by Predicting Treatment Outcomes, Validating Neoadjuvant Therapies, and Improving Precision.

Clinical Validation of Artificial Intelligence-Powered PD-L1 Tumor Proportion Score Interpretation for Immune Checkpoint Inhibitor Response Prediction in Non-Small Cell Lung Cancer.

PURPOSE: Evaluation of PD-L1 tumor proportion score (TPS) by pathologists has been very impactful bu...

[Prediction of recurrence-free survival in lung adenocarcinoma based on self-supervised pre-training and multi-task learning].

Computed tomography (CT) imaging is a vital tool for the diagnosis and assessment of lung adenocarci...

A novel single-port robot for total gastrectomy to treat gastric cancer: A case report (with video).

Multiport robots are now widely used for total gastrectomy for gastric cancer, while there is almost...

Advanced Technologies in Radiation Research.

The U.S. Government is committed to maintaining a robust research program that supports a portfolio ...

Association Between Body Composition and Survival in Patients With Gastroesophageal Adenocarcinoma: An Automated Deep Learning Approach.

PURPOSE: Body composition (BC) may play a role in outcome prognostication in patients with gastroeso...

Predicting Invasiveness of Lung Adenocarcinoma at Chest CT with Deep Learning Ternary Classification Models.

Background Preoperative discrimination of preinvasive, minimally invasive, and invasive adenocarcino...

D3EGFR: a webserver for deep learning-guided drug sensitivity prediction and drug response information retrieval for EGFR mutation-driven lung cancer.

As key oncogenic drivers in non-small-cell lung cancer (NSCLC), various mutations in the epidermal g...

Minimally invasive surgery for clinical T4 non-small-cell lung cancer: national trends and outcomes.

OBJECTIVES: Recent randomized data support the perioperative benefits of minimally invasive surgery ...

[Current status and prospects for the application of robot-assisted spine surgery].

Traditional spine surgery frequently encounters difficulties with inadequate surgical visualization ...

Towards an Explainable AI Platform to Study Interruptions in Cancer Radiation Therapy.

Radiation therapy interruptions drive cancer treatment failures; they represent an untapped opportun...

Deep learning for automated segmentation in radiotherapy: a narrative review.

The segmentation of organs and structures is a critical component of radiation therapy planning, wit...

Weakly Supervised Deep Learning Predicts Immunotherapy Response in Solid Tumors Based on PD-L1 Expression.

UNLABELLED: Programmed death-ligand 1 (PD-L1) IHC is the most commonly used biomarker for immunother...

Artificial Intelligence-suggested Predictive Model of Survival in Patients Treated With Stereotactic Radiotherapy for Early Lung Cancer.

BACKGROUND/AIM: Overall survival (OS)-predictive models to clinically stratify patients with stage I...

Machine Learning-derived Multi-omics Prognostic Signature of Pyroptosis-related lncRNA with Regard to ZKSCAN2-DT and Tumor Immune Infiltration in Colorectal Cancer.

BACKGROUND: Colorectal cancer (CRC) has become the most prevalent gastrointestinal malignant tumor, ...

The Future of MR-Guided Radiation Therapy.

Magnetic resonance image guided radiation therapy (MRIgRT) is a relatively new technology that has a...