Latest AI and machine learning research in lung cancer for healthcare professionals.
OBJECTIVES: Lung ultrasound reduces the number of chest X-rays after thoracic surgery and thus the r...
OBJECTIVE: The uPath PD-L1 (SP263) is an AI-based platform designed to aid pathologists in identifyi...
OBJECTIVES: To identify potential diagnostic markers for small cell lung cancer (SCLC) and investiga...
Machine- and patient-specific quality assurance (QA) is essential to ensure the safety and accuracy ...
In recent years, long non-coding RNAs (lncRNAs) have emerged as potential regulators of biological p...
The medical application of Computed Tomography (CT) is to provide detailed anatomical structures of ...
An automated knowledge modeling algorithm for Cancer Clinical Practice Guidelines (CPGs) extracts th...
Multiple instance learning(MIL) has shown superior performance in the classification of whole-slide ...
Accurate classification between tumor MicroSatellite Stability (MSS) and Instability (MSI) is crucia...
Providing robust prognosis predictions for cancers with limited data samples remains a challenge for...
Lung adenocarcinoma (LUAD) is a leading cause of cancer-related deaths, and improving prognostic acc...
INTRODUCTION: In this study, we aimed to evaluate the predictive value of circulating lymphocyte sub...
Lung adenocarcinoma (LUAD) is a tumour characterized by high tumour heterogeneity. Although there ar...
Electrical impedance tomography (EIT) is a non-radiation, non-invasive visual diagnostic technique. ...
Cosmic radiation exposure is one of the important health concerns for aircrews. In this work, we con...
Lung cancer, which accounts for about 18% of all cancer-related deaths worldwide, has a dismal 5-yea...
PURPOSE: To use modern machine learning approaches to enhance and automate the feature extraction fr...
BACKGROUND: Previous studies have indicated that creatinine (Cr)-based glomerular filtration rate (G...
Recent studies have extensively used deep learning algorithms to analyze gene expression to predict ...
This paper explores the potential of leveraging electronic health records (EHRs) for personalized he...
Tumor molecular data sets are becoming increasingly complex, making it nearly impossible for humans ...