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Subcategories: Asthma COPD Cystic Fibrosis Pneumonia Tuberculosis

Showing 3760-3780 of 6,659 articles

Deep learning-based automated detection algorithm for active pulmonary tuberculosis on chest radiographs: diagnostic performance in systematic screening of asymptomatic individuals.

OBJECTIVES: Performance of deep learning-based automated detection (DLAD) algorithms in systematic s...

Aug 2020 PMID: 32857202

Development and clinical implementation of tailored image analysis tools for COVID-19 in the midst of the pandemic: The synergetic effect of an open, clinically embedded software development platform and machine learning.

PURPOSE: During the emerging COVID-19 pandemic, radiology departments faced a substantial increase i...

Aug 2020 PMID: 32927416

Fully-Connected Neural Networks with Reduced Parameterization for Predicting Histological Types of Lung Cancer from Somatic Mutations.

Several challenges appear in the application of deep learning to genomic data. First, the dimensiona...

Aug 2020 PMID: 32872133

Knowledge Models as Teaching Aid for Training Intensity Modulated Radiation Therapy Planning: A Lung Cancer Case Study.

Artificial intelligence (AI) employs knowledge models that often behave as a black-box to the major...

Aug 2020 PMID: 33733183

Detection of pulmonary nodules based on a multiscale feature 3D U-Net convolutional neural network of transfer learning.

A new computer-aided detection scheme is proposed, the 3D U-Net convolutional neural network, based ...

Aug 2020 PMID: 32845877

Computer-Aided System for the Detection of Multicategory Pulmonary Tuberculosis in Radiographs.

The early screening and diagnosis of tuberculosis plays an important role in the control and treatme...

Aug 2020 PMID: 32908660

Development and Validation of a Modified Three-Dimensional U-Net Deep-Learning Model for Automated Detection of Lung Nodules on Chest CT Images From the Lung Image Database Consortium and Japanese Datasets.

RATIONALE AND OBJECTIVES: A more accurate lung nodule detection algorithm is needed. We developed a ...

Aug 2020 PMID: 32839096

Toward automated severe pharyngitis detection with smartphone camera using deep learning networks.

PURPOSE: Severe pharyngitis is frequently associated with inflammations caused by streptococcal phar...

Aug 2020 PMID: 32871294

Predicting bovine tuberculosis status of dairy cows from mid-infrared spectral data of milk using deep learning.

Bovine tuberculosis (bTB) is a zoonotic disease in cattle that is transmissible to humans, distribut...

Aug 2020 PMID: 32828515

Automatic lung segmentation in routine imaging is primarily a data diversity problem, not a methodology problem.

BACKGROUND: Automated segmentation of anatomical structures is a crucial step in image analysis. For...

Aug 2020 PMID: 32814998

Differentiating novel coronavirus pneumonia from general pneumonia based on machine learning.

BACKGROUND: Chest CT screening as supplementary means is crucial in diagnosing novel coronavirus pne...

Aug 2020 PMID: 32814568

Utilization of machine-learning models to accurately predict the risk for critical COVID-19.

Among patients with Coronavirus disease (COVID-19), the ability to identify patients at risk for det...

Aug 2020 PMID: 32812204

Artificial intelligence in thoracic surgery: past, present, perspective and limits.

Artificial intelligence (AI) technology is becoming prevalent in many areas of everyday life. The he...

Aug 2020 PMID: 32817112

Robot-assisted pelvic urologic surgeries: is it feasible to perform under reduced tilt?

To evaluate the feasibility and outcomes of performing robot-assisted pelvic surgery at a reduced an...

Aug 2020 PMID: 32803652

Detecting asthma exacerbations using daily home monitoring and machine learning.

OBJECTIVE: Acute exacerbations contribute significantly to the morbidity of asthma. Recent studies h...

Aug 2020 PMID: 32718193

Artificial intelligence for the detection of COVID-19 pneumonia on chest CT using multinational datasets.

Chest CT is emerging as a valuable diagnostic tool for clinical management of COVID-19 associated lu...

Aug 2020 PMID: 32796848

The deep learning model combining CT image and clinicopathological information for predicting ALK fusion status and response to ALK-TKI therapy in non-small cell lung cancer patients.

PURPOSE: This study aimed to investigate the deep learning model (DLM) combining computed tomography...

Aug 2020 PMID: 32794105

Identifying sarcopenia in advanced non-small cell lung cancer patients using skeletal muscle CT radiomics and machine learning.

BACKGROUND: Sarcopenia has been confirmed as a poor prognostic indicator of lung cancer. However, th...

Aug 2020 PMID: 32767522

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Deep learning-based automated detection algorithm for active pulmonary tuberculosis on chest radiographs: diagnostic performance in systematic screening of asymptomatic individuals.

Development and clinical implementation of tailored image analysis tools for COVID-19 in the midst of the pandemic: The synergetic effect of an open, clinically embedded software development platform and machine learning.

Fully-Connected Neural Networks with Reduced Parameterization for Predicting Histological Types of Lung Cancer from Somatic Mutations.

Knowledge Models as Teaching Aid for Training Intensity Modulated Radiation Therapy Planning: A Lung Cancer Case Study.

Detection of pulmonary nodules based on a multiscale feature 3D U-Net convolutional neural network of transfer learning.

Computer-Aided System for the Detection of Multicategory Pulmonary Tuberculosis in Radiographs.

Development and Validation of a Modified Three-Dimensional U-Net Deep-Learning Model for Automated Detection of Lung Nodules on Chest CT Images From the Lung Image Database Consortium and Japanese Datasets.

Toward automated severe pharyngitis detection with smartphone camera using deep learning networks.

Predicting bovine tuberculosis status of dairy cows from mid-infrared spectral data of milk using deep learning.

Automatic lung segmentation in routine imaging is primarily a data diversity problem, not a methodology problem.

Differentiating novel coronavirus pneumonia from general pneumonia based on machine learning.

Utilization of machine-learning models to accurately predict the risk for critical COVID-19.

Artificial intelligence in thoracic surgery: past, present, perspective and limits.

Robot-assisted pelvic urologic surgeries: is it feasible to perform under reduced tilt?

Detecting asthma exacerbations using daily home monitoring and machine learning.

Artificial intelligence for the detection of COVID-19 pneumonia on chest CT using multinational datasets.

The deep learning model combining CT image and clinicopathological information for predicting ALK fusion status and response to ALK-TKI therapy in non-small cell lung cancer patients.

Development and clinical application of deep learning model for lung nodules screening on CT images.

A machine learning and network framework to discover new indications for small molecules.

Prediction of respiratory decompensation in Covid-19 patients using machine learning: The READY trial.

Identifying sarcopenia in advanced non-small cell lung cancer patients using skeletal muscle CT radiomics and machine learning.

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