Pulmonology

Identification of transcription factors that may reprogram lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma is one of most threatening disease to human health. Although many efforts have been devoted to its genetic study, few researches have been focused on the transcription factors which regulate tumor initiation and progression by affecting multiple downstream gene transcription. It is proved that proper transcription factors may mediate the direct reprogramming of canc...

High-accuracy detection of airway obstruction in asthma using machine learning algorithms and forced oscillation measurements.

BACKGROUND AND OBJECTIVES: The main pathologic feature of asthma is episodic airway obstruction. This is usually detected by spirometry and body plethysmography. These tests, however, require a high degree of collaboration and maximal effort on the part of the patient. There is agreement in the literature that there is a demand of research into new technologies to improve non-invasive testing of l...

The attractor recurrent neural network based on fuzzy functions: An effective model for the classification of lung abnormalities.

The respiratory system dynamic is of high significance when it comes to the detection of lung abnormalities, which highlights the importance of presen...

Multiscale Rotation-Invariant Convolutional Neural Networks for Lung Texture Classification.

We propose a new multiscale rotation-invariant convolutional neural network (MRCNN) model for classifying various lung tissue types on high-resolution...

Feasibility of robotic stereotactic body radiotherapy of lung tumors with kilovoltage x-ray beams.

PURPOSE: Robotic Stereotactic body radiation therapy (SBRT) for lung tumors is treatment modality that, for cases of inoperable lung tumors, has shown...

A Natural Language Processing Framework for Assessing Hospital Readmissions for Patients With COPD.

With the passage of recent federal legislation, many medical institutions are now responsible for reaching target hospital readmission rates. Chronic ...

Extracting microRNA-gene relations from biomedical literature using distant supervision.

Many biomedical relation extraction approaches are based on supervised machine learning, requiring an annotated corpus. Distant supervision aims at tr...

Respiratory motion compensation for the robot-guided laser osteotome.

PURPOSE: The use of a robot-guided laser osteotome for median sternotomy is impeded by prohibiting cutting inaccuracies due to respiration-induced mot...

Prediction of Adverse Events in Patients Undergoing Major Cardiovascular Procedures.

Electronic health records (EHR) provide opportunities to leverage vast arrays of data to help prevent adverse events, improve patient outcomes, and re...

Prediction of Prolonged Ventilation after Coronary Artery Bypass Grafting: Data from an Artificial Neural Network.

OBJECTIVES: The need for mechanical ventilation 24 hours after coronary artery bypass grafting (CABG) is considered a morbidity by the Society of Thor...

Respiratory motion prediction and prospective correction for free-breathing arterial spin-labeled perfusion MRI of the kidneys.

PURPOSE: Respiratory motion prediction using an artificial neural network (ANN) was integrated with pseudocontinuous arterial spin labeling (pCASL) MR...

Physiological motion modeling for organ-mounted robots.

BACKGROUND: Organ-mounted robots passively compensate heartbeat and respiratory motion. In model-guided procedures, this motion can be a significant s...

Fifty years of computer analysis in chest imaging: rule-based, machine learning, deep learning.

Half a century ago, the term "computer-aided diagnosis" (CAD) was introduced in the scientific literature. Pulmonary imaging, with chest radiography a...

Design and analysis of a tendon-based computed tomography-compatible robot with remote center of motion for lung biopsy.

Nowadays, biopsy is a decisive method of lung cancer diagnosis, whereas lung biopsy is time-consuming, complex and inaccurate. So a computed tomograph...

Interpretable Deep Models for ICU Outcome Prediction.

Exponential surge in health care data, such as longitudinal data from electronic health records (EHR), sensor data from intensive care unit (ICU), etc...

Accelerating Chart Review Using Automated Methods on Electronic Health Record Data for Postoperative Complications.

Manual Chart Review (MCR) is an important but labor-intensive task for clinical research and quality improvement. In this study, aiming to accelerate ...

Controlling testing volume for respiratory viruses using machine learning and text mining.

Viral testing for pediatric inpatients with respiratory symptoms is common, with considerable associated charges. In an attempt to reduce testing volu...

A Belief Rule Based Expert System to Assess Tuberculosis under Uncertainty.

The primary diagnosis of Tuberculosis (TB) is usually carried out by looking at the various signs and symptoms of a patient. However, these signs and ...

Hybrid methodology for tuberculosis incidence time-series forecasting based on ARIMA and a NAR neural network.

Tuberculosis (TB) affects people globally and is being reconsidered as a serious public health problem in China. Reliable forecasting is useful for th...

Control and Evaluation of a Powered Transfemoral Prosthesis for Stair Ascent.

This paper assesses the metabolic effort exerted by three transfemoral amputees, when using a powered knee and ankle prosthesis for stair ascent, rela...