Oncology/Hematology

Lung Cancer

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

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Showing 169-189 of 8,029 articles
A novel model for predicting immunotherapy response and prognosis in NSCLC patients.

BACKGROUND: How to screen beneficiary populations has always been a clinical challenge in the treatm...

Machine learning models for predicting survival in lung cancer patients undergoing microwave ablation.

OBJECTIVE: To develop and validate predictive models assessing survival outcomes in patients with no...

Thorax-encompassing multi-modality PET/CT deep learning model for resected lung cancer prognostication: A retrospective, multicenter study.

BACKGROUND: Patients with early-stage non-small cell lung cancer (NSCLC) typically receive surgery a...

Detecting the left atrial appendage in CT localizers using deep learning.

Patients with cardioembolic stroke often undergo CT of the left atrial appendage (LAA), for example,...

Predicting Gene Comutation of EGFR and TP53 by Radiomics and Deep Learning in Patients With Lung Adenocarcinomas.

PURPOSE: This study was designed to construct progressive binary classification models based on radi...

A machine learning tool for prediction of vertebral compression fracture following stereotactic body radiation therapy for spinal metastases.

BACKGROUND AND PURPOSE: The most common adverse event following spine stereotactic body radiotherapy...

Assessing ChatGPT for clinical decision-making in radiation oncology, with open-ended questions and images.

PURPOSE: This study assesses the practicality and correctness of ChatGPT-4 and 4O's answers to clini...

Deep learning radiopathomics predicts targeted therapy sensitivity in EGFR-mutant lung adenocarcinoma.

BACKGROUND: Ttyrosine kinase inhibitors (TKIs) represent the standard first-line treatment for patie...

F-FDG PET/CT-based deep learning models and a clinical-metabolic nomogram for predicting high-grade patterns in lung adenocarcinoma.

BACKGROUND: To develop and validate deep learning (DL) and traditional clinical-metabolic (CM) model...

Reduction of radiation exposure in chest radiography using deep learning-based noise reduction processing: A phantom and retrospective clinical study.

INTRODUCTION: Intelligent noise reduction (INR), a deep learning-based noise reduction developed by ...

Options for postoperative radiation therapy in patients with de novo metastatic breast cancer.

BACKGROUND: Although meta-analyses have demonstrated survival benefits associated with primary tumor...

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