COPD

Digital Healthcare for Airway Diseases from Personal Environmental Exposure.

Digital technologies have emerged in various dimensions of human life, ranging from education to pro...

Rediscovery of the transcerebellar approach: improving the risk-benefit ratio in robot-assisted brainstem biopsies.

OBJECTIVE: Conventional frame-based stereotaxy through a transfrontal approach (TFA) is the gold sta...

Are robots the future? A case for robotic pyeloplasty as the gold standard treatment in ureteropelvic junction obstruction.

PURPOSE OF REVIEW: Robotic pyeloplasty is still a relatively novel procedure. Clinically, early stud...

[The accuracy and influencing factors of sleep staging based on single-channel EEG via a deep neural network].

To investigate theaccuracy of artificial intelligence sleep staging model in patients with habitual...

Histopathological Diagnosis System for Gastritis Using Deep Learning Algorithm.

Objective To develope a deep learning algorithm for pathological classification of chronic gastritis...

Predicting ventilator-associated pneumonia with machine learning.

Ventilator-associated pneumonia (VAP) is the most common and fatal nosocomial infection in intensive...

[A Case of Descending Colon and Rectal Cancer with Acute Myeloid Leukemia Performed Robot‒Assisted Hartmann's Procedure].

The case is a 68‒year‒old male, who had been diagnosed with acute myeloid leukemia(AML)prior to rect...

Area under the expiratory flow-volume curve: predicted values by regression and deep learning methods and recommendations for clinical practice.

BACKGROUND: In spirometry, the area under expiratory flow-volume curve (AEX-FV) was found to perform...

Swarming behavior and in vivo monitoring of enzymatic nanomotors within the bladder.

Enzyme-powered nanomotors are an exciting technology for biomedical applications due to their abilit...

[Application of deep learning-based chest CT auxiliary diagnosis system in emergency trauma patients].

To investigate the diagnostic efficacy and potential application value of deep learning-based chest...

The Gene Ontology resource: enriching a GOld mine.

The Gene Ontology Consortium (GOC) provides the most comprehensive resource currently available for ...

The Regimen of Computed Tomography Screening for Lung Cancer: Lessons Learned Over 25 Years From the International Early Lung Cancer Action Program.

We learned many unanticipated and valuable lessons since we started planning our study of low-dose c...

Postural Balance Evaluation in Patients with Chronic Obstructive Pulmonary Disease.

BACKGROUND: The risk of falling in patients with chronic obstructive pulmonary disease (COPD) is hig...

[Risk factors for postoperative intestinal obstruction in patients undergoing robot-assisted laparoscopic radical prostatectomy].

To analyze the risk factors of postoperative intestinal obstruction (POI) in patients undergoing ro...

Machine Learning Predictions of COPD Mortality: Computational Hide and Seek.

Relational Modeling for Robust and Efficient Pulmonary Lobe Segmentation in CT Scans.

Pulmonary lobe segmentation in computed tomography scans is essential for regional assessment of pul...

The efficacy of support vector machines in modelling deviations from the Beer-Lambert law for optical measurement of lactate.

Lactate is an important biomarker with a significant diagnostic and prognostic ability in relation t...

Machine Learning/Deep Neuronal Network: Routine Application in Chest Computed Tomography and Workflow Considerations.

The constantly increasing number of computed tomography (CT) examinations poses major challenges for...

Artificial Intelligence-based Fully Automated Per Lobe Segmentation and Emphysema-quantification Based on Chest Computed Tomography Compared With Global Initiative for Chronic Obstructive Lung Disease Severity of Smokers.

OBJECTIVES: The objective of this study was to evaluate an artificial intelligence (AI)-based protot...

[Quantitative Analysis of Emphysema in Ultra-high-resolution CT by Using Deep Learning Reconstruction: Comparison with Hybrid Iterative Reconstruction].

PURPOSE: The noise generated in ultra-high-resolution computed tomography (U-HRCT) images affects th...

Machine Learning and the Cancer-Diagnosis Problem - No Gold Standard.