Pulmonology

Unsupervised Deep Learning Features for Lung Cancer Overall Survival Analysis.

Lung cancer overall survival analysis using computed tomography (CT) images plays an important role in treatment planning. Most current analysis methods involve hand-crafted image features for survival time prediction. However, hand-crafted features require domain knowledge and may lack specificity to lung cancer. Advanced self-learning models such as deep learning have showed superior performance...

SpiroConfidence: Determining the Validity of Smartphone Based Spirometry Using Machine Learning.

Prior work has shown that smartphone spirometry can effectively measure lung function using the phone's built-in microphone and could one day play a critical role in making spirometry more usable, accessible, and cost-effective. Although traditional spirometry is performed with the guidance of a medical expert, smartphone spirometry lacks the ability to provide the patient feedback or guarantee th...

A Fully Convolutional Deep Neural Network for Lung Tumor Boundary Tracking in MRI.

Delineation of lung tumor from adjacent tissue from a series of magnetic resonance images (MRI) poses many difficulties due to the image similarities ...

[Comparison of machine learning method and logistic regression model in prediction of acute kidney injury in severely burned patients].

To build risk prediction models for acute kidney injury (AKI) in severely burned patients, and to compare the prediction performance of machine learn...

Robotic right middle lobectomy with a subxiphoid utility port.

We present the case of a 74-year-old man with Stage IIa pulmonary adenocarcinoma, for which he underwent a robotic right middle lobectomy. A 4-armed, ...

Machine learning for classifying tuberculosis drug-resistance from DNA sequencing data.

MOTIVATION: Correct and rapid determination of Mycobacterium tuberculosis (MTB) resistance against available tuberculosis (TB) drugs is essential for ...

Using Unsupervised Machine Learning to Identify Subgroups Among Home Health Patients With Heart Failure Using Telehealth.

This study explored the use of unsupervised machine learning to identify subgroups of patients with heart failure who used telehealth services in the ...

Data-Adaptive Estimation for Double-Robust Methods in Population-Based Cancer Epidemiology: Risk Differences for Lung Cancer Mortality by Emergency Presentation.

In this paper, we propose a structural framework for population-based cancer epidemiology and evaluate the performance of double-robust estimators for...

[A Paired Case Controlled Study Comparing the Short-term Outcomes of Da Vinci RATS and VATS Approach for Non-small Cell Lung Cancer].

BACKGROUND: Da Vinci Surgical System is one of the greatest inventions of the 20th century, which represents the development direction of the precise ...

Artificial intelligence in diagnosis of obstructive lung disease: current status and future potential.

PURPOSE OF REVIEW: The application of artificial intelligence in the diagnosis of obstructive lung diseases is an exciting phenomenon. Artificial inte...

Detection of tuberculosis patterns in digital photographs of chest X-ray images using Deep Learning: feasibility study.

OBJECTIVE: To evaluate the feasibility of Deep Learning-based detection and classification of pathological patterns in a set of digital photographs of...

Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning.

The implementation of clinical-decision support algorithms for medical imaging faces challenges with reliability and interpretability. Here, we establ...

Automatic Calcium Scoring in Low-Dose Chest CT Using Deep Neural Networks With Dilated Convolutions.

Heavy smokers undergoing screening with low-dose chest CT are affected by cardiovascular disease as much as by lung cancer. Low-dose chest CT scans ac...

A hybrid CNN feature model for pulmonary nodule malignancy risk differentiation.

The malignancy risk differentiation of pulmonary nodule is one of the most challenge tasks of computer-aided diagnosis (CADx). Most recently reported ...

Discovering Pediatric Asthma Phenotypes on the Basis of Response to Controller Medication Using Machine Learning.

RATIONALE: Pediatric asthma has variable underlying inflammation and symptom control. Approaches to addressing this heterogeneity, such as clustering ...

Low dose CT reconstruction via L1 norm dictionary learning using alternating minimization algorithm and balancing principle.

Excessive radiation exposure in computed tomography (CT) scans increases the chance of developing cancer and has become a major clinical concern. Rece...

Handmade trileaflet valve design and validation for patch-valved conduit reconstruction using generalized regression machine learning model.

Pulmonary valve diseases include the different degrees of aortic stenosis or congenital defects in children or adults. Valve repair or replacement sur...

[RETROPERITONEAL LIPOSARCOMA WITH MULTIPLE RECURRENCE OF LUNG METASTASES TREATED BY MULTIMODAL THERAPY CENTERING ON THE OPERATION: A CASE REPORT].

A 34-year-old man presented with scrotal pain and slight fever. The scrotal pain was improved by the treatment of antibiotics, but the slight fever re...

Association of Procalcitonin Value and Bacterial Coinfections in Pediatric Patients With Viral Lower Respiratory Tract Infections Admitted to the Pediatric Intensive Care Unit.

OBJECTIVE: Our primary objective was to determine the utility of procalcitonin (PCT) in detection of bacterial coinfection in children < 5 years admit...

The Effects of Mouth Opening and Throat Pack Placement on Uncuffed Nasal Endotracheal Tube Leakage and Delivered Tidal Volumes in Mechanically Ventilated Pediatric Patients Undergoing Dental Procedures.

Intubation for pediatric patients is frequently performed with an uncuffed endotracheal tube (ETT), which may result in an incomplete tracheal seal, r...