AIMC Topic: Lung Neoplasms

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Comparison between robot-assisted thoracoscopic surgery and video-assisted thoracoscopic surgery for mediastinal and hilar lymph node dissection in lung cancer surgery.

Interactive cardiovascular and thoracic surgery
OBJECTIVES: Lymph node dissection (LND) with robot-assisted thoracoscopic surgery (RATS) in lung cancer surgery has not been fully evaluated. The aim of this study was to compare LND surgical results between video-assisted thoracoscopic surgery (VATS...

Machine Learning for Early Lung Cancer Identification Using Routine Clinical and Laboratory Data.

American journal of respiratory and critical care medicine
Most lung cancers are diagnosed at an advanced stage. Presymptomatic identification of high-risk individuals can prompt earlier intervention and improve long-term outcomes. To develop a model to predict a future diagnosis of lung cancer on the basi...

Long-term and short-term outcomes of robot- versus video-assisted anatomic lung resection in lung cancer: a systematic review and meta-analysis.

European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery
OBJECTIVES: Minimally invasive thoracic surgery has evolved with the introduction of robotic platforms. This study aimed to compare the long-term and short-term outcomes of the robot-assisted thoracic surgery (RATS) and video-assisted thoracic surger...

Evaluation of a deep learning-based computer-aided detection algorithm on chest radiographs: Case-control study.

Medicine
Along with recent developments in deep learning techniques, computer-aided diagnosis (CAD) has been growing rapidly in the medical imaging field. In this work, we evaluate the deep learning-based CAD algorithm (DCAD) for detecting and localizing 3 ma...

Automated approach for segmenting gross tumor volumes for lung cancer stereotactic body radiation therapy using CT-based dense V-networks.

Journal of radiation research
The aim of this study was to develop an automated segmentation approach for small gross tumor volumes (GTVs) in 3D planning computed tomography (CT) images using dense V-networks (DVNs) that offer more advantages in segmenting smaller structures than...

Independent Validation of a Comprehensive Machine Learning Approach Predicting Survival After Radiotherapy for Bone Metastases.

Anticancer research
BACKGROUND/AIM: The aim of this study was to analyze the survival predictions obtained from a web platform allowing for computation of the so-called Bone Metastases Ensemble Trees for Survival (BMETS). This prediction model is based on a machine lear...

Key Principles of Clinical Validation, Device Approval, and Insurance Coverage Decisions of Artificial Intelligence.

Korean journal of radiology
Artificial intelligence (AI) will likely affect various fields of medicine. This article aims to explain the fundamental principles of clinical validation, device approval, and insurance coverage decisions of AI algorithms for medical diagnosis and p...

[A deep learning-based lung nodule density classification and segmentation method and its effectiveness under different CT reconstruction algorithms].

Zhonghua yi xue za zhi
To evaluate the diagnostic value of the lung nodule classification and segmentation algorithm based on deep learning among different CT reconstruction algorithms. Chest CT of 363 patients from June 2019 to September 2019 in Radiology Department of ...