Pulmonology

Deploying Machine Learning Models Using Progressive Web Applications: Implementation Using a Neural Network Prediction Model for Pneumonia Related Child Mortality in The Gambia.

BACKGROUND: Translating research outputs into practical tools for medical practitioners is a neglect...

Evaluation of domain generalization and adaptation on improving model robustness to temporal dataset shift in clinical medicine.

Temporal dataset shift associated with changes in healthcare over time is a barrier to deploying mac...

Reintubation Summation Calculation: A Predictive Score for Extubation Failure in Critically Ill Patients.

OBJECTIVE: To derive and validate a multivariate risk score for the prediction of respiratory failur...

Subcutaneous emphysema and negative-pressure pulmonary edema after robot-assisted bladder enlargement: A case report.

COPD identification and grading based on deep learning of lung parenchyma and bronchial wall in chest CT images.

OBJECTIVE: Chest CT can display the main pathogenic factors of chronic obstructive pulmonary disease...

A machine learning model for predicting deterioration of COVID-19 inpatients.

The COVID-19 pandemic has been spreading worldwide since December 2019, presenting an urgent threat ...

A deep learning-based system capable of detecting pneumothorax via electrocardiogram.

PURPOSE: To determine if an electrocardiogram-based artificial intelligence system can identify pneu...

Early heart rate variability evaluation enables to predict ICU patients' outcome.

Heart rate variability (HRV) is a mean to evaluate cardiac effects of autonomic nervous system activ...

Deep-learning-assisted Fourier transform imaging spectroscopy for hyperspectral fluorescence imaging.

Hyperspectral fluorescence imaging is widely used when multiple fluorescent probes with close emissi...

Artificial Intelligence-Aided Diagnosis Software to Identify Highly Suspicious Pulmonary Nodules.

INTRODUCTION: To evaluate the value of artificial intelligence (AI)-assisted software in the diagnos...

Accurate and rapid prediction of tuberculosis drug resistance from genome sequence data using traditional machine learning algorithms and CNN.

Effective and timely antibiotic treatment depends on accurate and rapid in silico antimicrobial-resi...

Artificial intelligence in positioning between mandibular third molar and inferior alveolar nerve on panoramic radiography.

Determining the exact positional relationship between mandibular third molar (M3) and inferior alveo...

An Efficient Deep Learning Model to Detect COVID-19 Using Chest X-ray Images.

The tragic pandemic of COVID-19, due to the Severe Acute Respiratory Syndrome coronavirus-2 or SARS-...

Mechanism Analysis and Self-Adaptive RBFNN Based Hybrid Soft Sensor Model in Energy Production Process: A Case Study.

Despite hard sensors can be easily used in various condition monitoring of energy production process...

Production of Bioactive Substances to Alleviates Hangover and Ethanol-Induced Liver Damage through Fermentation of Using .

The purpose of this study is to evaluate the effect of the bioconversion products of extract fermen...

Open, Video- and Robot-Assisted Thoracoscopic Lobectomy for Stage II-IIIA Non-Small Cell Lung Cancer.

BACKGROUND: This study compares the short- and long-term outcomes of open vs robotic vs video-assist...

Comparison of error rates between four pretrained DenseNet convolutional neural network models and 13 board-certified veterinary radiologists when evaluating 15 labels of canine thoracic radiographs.

Convolutional neural networks (CNNs) are commonly used as artificial intelligence (AI) tools for eva...

Development of Deep Learning-based Automatic Scan Range Setting Model for Lung Cancer Screening Low-dose CT Imaging.

RATIONALE AND OBJECTIVES: To develop an automatic setting of a deep learning-based system for detect...

Chest X-ray Classification for the Detection of COVID-19 Using Deep Learning Techniques.

Recent technological developments pave the path for deep learning-based techniques to be used in alm...

Predicting EGFR mutation status by a deep learning approach in patients with non-small cell lung cancer brain metastases.

PURPOSE: Non-small cell lung cancer (NSCLC) tends to metastasize to the brain. Between 10 and 60% of...

Multiparametric Quantitative US Examination of Liver Fibrosis: A Feature-Engineering and Machine-Learning Based Analysis.

Quantitative ultrasound (QUS), which attempts to extract quantitative features from the US radiofreq...