AIMC Topic: Lung Neoplasms

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Histological Subtypes Classification of Lung Cancers on CT Images Using 3D Deep Learning and Radiomics.

Academic radiology
RATIONALE AND OBJECTIVES: Histological subtypes of lung cancers are critical for clinical treatment decision. In this study, we attempt to use 3D deep learning and radiomics methods to automatically distinguish lung adenocarcinomas (ADC), squamous ce...

Intraoperative complications and troubles in robot-assisted anatomical pulmonary resection.

General thoracic and cardiovascular surgery
OBJECTIVE: Regarding intraoperative complications and troubles during robot-assisted thoracic surgery, few data are available especially in Japan. This study was aimed to elucidate intraoperative complications and troubles in robotic anatomical lung ...

The major effects of health-related quality of life on 5-year survival prediction among lung cancer survivors: applications of machine learning.

Scientific reports
The primary goal of this study was to evaluate the major roles of health-related quality of life (HRQOL) in a 5-year lung cancer survival prediction model using machine learning techniques (MLTs). The predictive performances of the models were compar...

An Artificial Intelligence Model for Predicting 1-Year Survival of Bone Metastases in Non-Small-Cell Lung Cancer Patients Based on XGBoost Algorithm.

BioMed research international
Non-small-cell lung cancer (NSCLC) patients often develop bone metastases (BM), and the overall survival for these patients is usually perishing. However, a model with high accuracy for predicting the survival of NSCLC with BM is still lacking. Here,...

Deep learning combined with radiomics may optimize the prediction in differentiating high-grade lung adenocarcinomas in ground glass opacity lesions on CT scans.

European journal of radiology
PURPOSE: Adenocarcinoma (ADC) is the most common histological subtype of lung cancers in non-small cell lung cancer (NSCLC) in which ground glass opacifications (GGOs) found on computed tomography (CT) scans are the most common lesions. However, the ...

Artificial intelligence-based collaborative filtering method with ensemble learning for personalized lung cancer medicine without genetic sequencing.

Pharmacological research
In personalized medicine, many factors influence the choice of compounds. Hence, the selection of suitable medicine for patients with non-small-cell lung cancer (NSCLC) is expensive. To shorten the decision-making process for compounds, we propose a ...

Perioperative outcomes of robot-assisted vs video-assisted and traditional open thoracic surgery for lung cancer: A systematic review and network meta-analysis.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: The superiority of robot-assisted thoracic surgery (RATS) over video-assisted thoracic surgery (VATS) and thoracotomy remains controversial for lung cancer.

Deep learning-based pulmonary nodule detection: Effect of slab thickness in maximum intensity projections at the nodule candidate detection stage.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: To investigate the effect of the slab thickness in maximum intensity projections (MIPs) on the candidate detection performance of a deep learning-based computer-aided detection (DL-CAD) system for pulmonary nodule detection ...