AIMC Topic: Lung Neoplasms

Clear Filters Showing 1661 to 1670 of 1778 articles

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 ...

[Robot-assisted thoracic surgery-Areas of application and limitations].

Der Chirurg; Zeitschrift fur alle Gebiete der operativen Medizen
The proportion of robot-assisted thoracic surgery (RATS) is continuously increasing. The main areas of clinical application are anatomical lung resections with lymphadenectomy and resection of mediastinal tumors. Especially in the area of the thymus ...

Can a Novel Deep Neural Network Improve the Computer-Aided Detection of Solid Pulmonary Nodules and the Rate of False-Positive Findings in Comparison to an Established Machine Learning Computer-Aided Detection?

Investigative radiology
OBJECTIVE: The aim of this study was to compare the performance of 2 approved computer-aided detection (CAD) systems for detection of pulmonary solid nodules (PSNs) in an oncologic cohort. The first CAD system is based on a conventional machine learn...