AIMC Topic: Lung

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Deep learning classifiers for computer-aided diagnosis of multiple lungs disease.

Journal of X-ray science and technology
BACKGROUND: Computer aided diagnosis has gained momentum in the recent past. The advances in deep learning and availability of huge volumes of data along with increased computational capabilities has reshaped the diagnosis and prognosis procedures.

Autosegmentation of lung computed tomography datasets using deep learning U-Net architecture.

Journal of cancer research and therapeutics
AIM: Current radiotherapy treatment techniques require a large amount of imaging data for treatment planning which demand significant clinician's time to segment target volume and organs at risk (OARs). In this study, we propose to use U-net-based ar...

[Introduction of Robot-assisted Lung Segmentectomy].

Kyobu geka. The Japanese journal of thoracic surgery
Robot-assisted lung segmentectomy will be covered by insurance starting 2020. The results of the Japan Clinical Oncology Group( JCOG) 0802 trial have been reported, and the use of robot-assisted lung segmentectomy is expected to increase in the futur...

Deep Learning-based Outcome Prediction in Progressive Fibrotic Lung Disease Using High-Resolution Computed Tomography.

American journal of respiratory and critical care medicine
Reliable outcome prediction in patients with fibrotic lung disease using baseline high-resolution computed tomography (HRCT) data remains challenging. To evaluate the prognostic accuracy of a deep learning algorithm (SOFIA [Systematic Objective Fib...

[Lung parenchyma segmentation based on double scale parallel attention network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
[]Automatic and accurate segmentation of lung parenchyma is essential for assisted diagnosis of lung cancer. In recent years, researchers in the field of deep learning have proposed a number of improved lung parenchyma segmentation methods based on U...

Transfer Learning for Automated COVID-19 B-Line Classification in Lung Ultrasound.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Lung ultrasound (LUS) as a diagnostic tool is gaining support for its role in the diagnosis and management of COVID-19 and a number of other lung pathologies. B-lines are a predominant feature in COVID-19, however LUS requires a skilled clinician to ...

CellDART: cell type inference by domain adaptation of single-cell and spatial transcriptomic data.

Nucleic acids research
Deciphering the cellular composition in genome-wide spatially resolved transcriptomic data is a critical task to clarify the spatial context of cells in a tissue. In this study, we developed a method, CellDART, which estimates the spatial distributio...

Natural Language Processing to Identify Abnormal Breast, Lung, and Cervical Cancer Screening Test Results from Unstructured Reports to Support Timely Follow-up.

Studies in health technology and informatics
Cancer screening and timely follow-up of abnormal results can reduce mortality. One barrier to follow-up is the failure to identify abnormal results. While EHRs have coded results for certain tests, cancer screening results are often stored in free-t...

CapsNet-COVID19: Lung CT image classification method based on CapsNet model.

Mathematical biosciences and engineering : MBE
The outbreak of the Corona Virus Disease 2019 (COVID-19) has posed a serious threat to human health and life around the world. As the number of COVID-19 cases continues to increase, many countries are facing problems such as errors in nucleic acid te...

Lung Cancer Detection Using Machine Learning Techniques.

Critical reviews in biomedical engineering
Cancer has been the deadliest of diseases since decades constituting a large number of deaths annually. Lung cancer remains one of the most significant public health issues, accounting for a substantial proportion of cancer-related deaths globally. D...