Pulmonology

Lower Incidence of Postoperative Pulmonary Complications Following Robot-Assisted Minimally Invasive Esophagectomy for Esophageal Cancer: Propensity Score-Matched Comparison to Conventional Minimally Invasive Esophagectomy.

BACKGROUND: Whether robot-assisted minimally invasive surgery (RAMIE) is more beneficial than conventional minimally invasive surgery (MIE) remains unclear.

Hydroxyl Radical Generation Through the Fenton-Like Reaction of Hematin- and Catechol-Functionalized Microgels.

Hydroxyl radical (OH) is a potent reactive oxygen species with the ability to degrade hazardous organic compounds, kill bacteria, and inactivate viruses. However, an off-the-shelf, portable, and easily activated biomaterial for generating OH does not exist. Here, microgels were functionalized with catechol, an adhesive moiety found in mussel adhesive proteins, and hematin (HEM), a hydroxylated Fe ...

Pilot Study of Robot-Assisted Teleultrasound Based on 5G Network: A New Feasible Strategy for Early Imaging Assessment During COVID-19 Pandemic.

Early diagnosis is critical for the prevention and control of the coronavirus disease 2019 (COVID-19). We attempted to apply a protocol using teleultr...

Artificial intelligence techniques in asthma: a systematic review and critical appraisal of the existing literature.

Artificial intelligence (AI) when coupled with large amounts of well characterised data can yield models that are expected to facilitate clinical prac...

Prognostic importance of Kidney, Heart and Interstitial lung diseases (KHI triad) in PH: A machine learning study.

BACKGROUND: Pulmonary hypertension (PH) is a heterogeneous, severe and progressive disease with an impact on quality of life and life-expectancy despi...

Deep Learning Using Chest Radiographs to Identify High-Risk Smokers for Lung Cancer Screening Computed Tomography: Development and Validation of a Prediction Model.

BACKGROUND: Lung cancer screening with chest computed tomography (CT) reduces lung cancer death. Centers for Medicare & Medicaid Services (CMS) eligib...

Validation of a Deep Learning Algorithm for the Detection of Malignant Pulmonary Nodules in Chest Radiographs.

IMPORTANCE: The improvement of pulmonary nodule detection, which is a challenging task when using chest radiographs, may help to elevate the role of c...

Changes in body composition and substrate utilization after a short-term ketogenic diet in endurance-trained males.

Few studies have investigated the short-term effects of a very low carbohydrate ketogenic diet (KD) on body composition and substrate utilization in t...

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 screening for active pulmonary tuberculosis is unkn...

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 in chest CT admissions coupled with the novel deman...

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 dimensionality of input can be orders of magnitude greater t...

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 majority of users and are not designed to improve the s...

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 on multiscale features of transfer learning to aut...

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 treatment of tuberculosis infections. In this paper, an i...

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 modified three-dimensional (3D) U-net deep-learnin...

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, distributed worldwide, and considered endemic throughout mu...

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

PURPOSE: Severe pharyngitis is frequently associated with inflammations caused by streptococcal pharyngitis, which can cause immune-mediated and post-...

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 lung segmentation in computed tomography, a varie...

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

BACKGROUND: Chest CT screening as supplementary means is crucial in diagnosing novel coronavirus pneumonia (COVID-19) with high sensitivity and popula...

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 deterioration during their hospital stay is essential...