Pulmonology

Identification of Novel Genes in Human Airway Epithelial Cells associated with Chronic Obstructive Pulmonary Disease (COPD) using Machine-Based Learning Algorithms.

The aim of this project was to identify candidate novel therapeutic targets to facilitate the treatment of COPD using machine-based learning (ML) algorithms and penalized regression models. In this study, 59 healthy smokers, 53 healthy non-smokers and 21 COPD smokers (9 GOLD stage I and 12 GOLD stage II) were included (n = 133). 20,097 probes were generated from a small airway epithelium (SAE) mic...

Low vitamin D at ICU admission is associated with cancer, infections, acute respiratory insufficiency, and liver failure.

OBJECTIVES: Vitamin D deficiency may be associated with comorbidities and poor prognosis. However, this association in patients in the intensive care unit (ICU) has not been fully elucidated. The aim of this study was to investigate whether the serum concentrations of 25-hydroxyvitamin D (25[OH]D) within the first 48 h after ICU admission are associated with prognostic indicators (Acute Physiology...

Prediction and functional analysis of prokaryote lysine acetylation site by incorporating six types of features into Chou's general PseAAC.

Lysine acetylation is one of the most important types of protein post-translational modifications (PTM) that are widely involved in cellular regulator...

Analysis of tuberculosis disease through Raman spectroscopy and machine learning.

We present the effectiveness of Raman spectroscopy (RS) in combination with machine learning for screening and analysis of blood sera collected from t...

Comparisons of Pressure-controlled Ventilation with Volume Guarantee and Volume-controlled 1:1 Equal Ratio Ventilation on Oxygenation and Respiratory Mechanics during Robot-assisted Laparoscopic Radical Prostatectomy: a Randomized-controlled Trial.

During robot-assisted laparoscopic radical prostatectomy (RALP), steep Trendelenburg position and carbon dioxide pneumoperitoneum are inevitable for ...

Improvement of fully automated airway segmentation on volumetric computed tomographic images using a 2.5 dimensional convolutional neural net.

We propose a novel airway segmentation method in volumetric chest computed tomography (CT) and evaluate its performance on multiple datasets. The segm...

Knowledge-based Collaborative Deep Learning for Benign-Malignant Lung Nodule Classification on Chest CT.

The accurate identification of malignant lung nodules on chest CT is critical for the early detection of lung cancer, which also offers patients the b...

Machine learning and structural analysis of Mycobacterium tuberculosis pan-genome identifies genetic signatures of antibiotic resistance.

Mycobacterium tuberculosis is a serious human pathogen threat exhibiting complex evolution of antimicrobial resistance (AMR). Accordingly, the many pu...

Automatic lung nodule detection using a 3D deep convolutional neural network combined with a multi-scale prediction strategy in chest CTs.

OBJECTIVE: A novel computer-aided detection (CAD) scheme for lung nodule detection using a 3D deep convolutional neural network combined with a multi-...

Detecting drug-resistant tuberculosis in chest radiographs.

PURPOSE: Tuberculosis is a major global health threat claiming millions of lives each year. While the total number of tuberculosis cases has been decr...

3D Deep Learning from CT Scans Predicts Tumor Invasiveness of Subcentimeter Pulmonary Adenocarcinomas.

: Identification of early-stage pulmonary adenocarcinomas before surgery, especially in cases of subcentimeter cancers, would be clinically important ...

Sociomarkers and biomarkers: predictive modeling in identifying pediatric asthma patients at risk of hospital revisits.

The importance of social components of health has been emphasized both in epidemiology and public health. This paper highlights the significant impact...

Machine learning based framework to predict cardiac arrests in a paediatric intensive care unit : Prediction of cardiac arrests.

A cardiac arrest is a life-threatening event, often fatal. Whilst clinicians classify some of the cardiac arrests as potentially predictable, the majo...

Artificial neural network algorithm model as powerful tool to predict acute lung injury following to severe acute pancreatitis.

OBJECTIVE: The aim of this study is to predict the risk of severe acute pancreatitis (SAP) associated with acute lung injury (ALI) by artificial neura...

Development and Validation of Deep Learning-based Automatic Detection Algorithm for Malignant Pulmonary Nodules on Chest Radiographs.

Purpose To develop and validate a deep learning-based automatic detection algorithm (DLAD) for malignant pulmonary nodules on chest radiographs and to...

Using Artificial Intelligence (Watson for Oncology) for Treatment Recommendations Amongst Chinese Patients with Lung Cancer: Feasibility Study.

BACKGROUND: Artificial intelligence (AI) is developing quickly in the medical field and can benefit both medical staff and patients. The clinical deci...

Creation of a Robust and Generalizable Machine Learning Classifier for Patient Ventilator Asynchrony.

BACKGROUND: As healthcare increasingly digitizes, streaming waveform data is being made available from an variety of sources, but there still remains ...

Therapeutic Enoxaparin in the Morbidly Obese Patient: A Case Report and Review of the Literature.

Enoxaparin is a low molecular weight heparin commonly used in the treatment of venous thromboembolisms (VTEs); however, evidence on optimal empiric do...

Comprehensive urinary metabolomic characterization of a genetically induced mouse model of prostatic inflammation.

Dysfunction of the lower urinary tract commonly afflicts the middle-aged and aging male population. The etiology of lower urinary tract symptoms (LUTS...

Improving Prediction of Risk of Hospital Admission in Chronic Obstructive Pulmonary Disease: Application of Machine Learning to Telemonitoring Data.

BACKGROUND: Telemonitoring of symptoms and physiological signs has been suggested as a means of early detection of chronic obstructive pulmonary disea...