AIMC Topic: Lung Neoplasms
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Deep Convolutional Hashing for Low-Dimensional Binary Embedding of Histopathological Images.
IEEE journal of biomedical and health informatics
Apr 16, 2018
Compact binary representations of histopa-thology images using hashing methods provide efficient approximate nearest neighbor search for direct visual query in large-scale databases. They can be utilized to measure the probability of the abnormality ...
Spatial extreme learning machines: An application on prediction of disease counts.
Statistical methods in medical research
Apr 9, 2018
Extreme learning machines have gained a lot of attention by the machine learning community because of its interesting properties and computational advantages. With the increase in collection of information nowadays, many sources of data have missing ...
Functional-guided radiotherapy using knowledge-based planning.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Apr 5, 2018
BACKGROUND AND PURPOSE: There are two significant challenges when implementing functional-guided radiotherapy using 4DCT-ventilation imaging: (1) lack of knowledge of realistic patient specific dosimetric goals for functional lung and (2) ensuring co...
A deep 3D residual CNN for false-positive reduction in pulmonary nodule detection.
Medical physics
Mar 25, 2018
PURPOSE: The automatic detection of pulmonary nodules using CT scans improves the efficiency of lung cancer diagnosis, and false-positive reduction plays a significant role in the detection. In this paper, we focus on the false-positive reduction tas...
Localized thin-section CT with radiomics feature extraction and machine learning to classify early-detected pulmonary nodules from lung cancer screening.
Physics in medicine and biology
Mar 14, 2018
Lung cancer screening aims to detect small pulmonary nodules and decrease the mortality rate of those affected. However, studies from large-scale clinical trials of lung cancer screening have shown that the false-positive rate is high and positive pr...
Video-assisted thoracoscopic surgery versus robot-assisted thoracoscopic surgery versus thoracotomy for early-stage lung cancer.
The Journal of thoracic and cardiovascular surgery
Mar 2, 2018
Agile convolutional neural network for pulmonary nodule classification using CT images.
International journal of computer assisted radiology and surgery
Feb 23, 2018
OBJECTIVE: To distinguish benign from malignant pulmonary nodules using CT images is critical for their precise diagnosis and treatment. A new Agile convolutional neural network (CNN) framework is proposed to conquer the challenges of a small-scale m...
Role of artificial intelligence in the care of patients with nonsmall cell lung cancer.
European journal of clinical investigation
Feb 19, 2018
BACKGROUND: Lung cancer is the leading cause of cancer death worldwide. In up to 57% of patients, it is diagnosed at an advanced stage and the 5-year survival rate ranges between 10%-16%. There has been a significant amount of research using machine ...
An expert system design to diagnose cancer by using a new method reduced rule base.
Computer methods and programs in biomedicine
Feb 3, 2018
BACKGROUND AND OBJECTIVES: A Medical Expert System (MES) was developed which uses Reduced Rule Base to diagnose cancer risk according to the symptoms in an individual. A total of 13 symptoms were used. With the new MES, the reduced rules are controll...
A Risk Stratification Model for Lung Cancer Based on Gene Coexpression Network and Deep Learning.
BioMed research international
Jan 16, 2018
Risk stratification model for lung cancer with gene expression profile is of great interest. Instead of previous models based on individual prognostic genes, we aimed to develop a novel system-level risk stratification model for lung adenocarcinoma b...
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