COPD

Environmental and clinical data utility in pediatric asthma exacerbation risk prediction models.

BACKGROUND: Asthma exacerbations are triggered by a variety of clinical and environmental factors, but their relative impacts on exacerbation risk are unclear. There is a critical need to develop methods to identify children at high-risk for future exacerbation to allow targeted prevention measures. We sought to evaluate the utility of models using spatiotemporally resolved climatic data and indiv...

Deep learning for spirometry quality assurance with spirometric indices and curves.

BACKGROUND: Spirometry quality assurance is a challenging task across levels of healthcare tiers, especially in primary care. Deep learning may serve as a support tool for enhancing spirometry quality. We aimed to develop a high accuracy and sensitive deep learning-based model aiming at assisting high-quality spirometry assurance.

A Challenge for Emphysema Quantification Using a Deep Learning Algorithm With Low-dose Chest Computed Tomography.

PURPOSE: We aimed to identify clinically relevant deep learning algorithms for emphysema quantification using low-dose chest computed tomography (LDCT...

Can Hyperspectral Imaging and Neural Network Classification Be Used for Ore Grade Discrimination at the Point of Excavation?

This work determines whether hyperspectral imaging is suitable for discriminating ore from waste at the point of excavation. A prototype scanning syst...

Deep learning model can improve the diagnosis rate of endoscopic chronic atrophic gastritis: a prospective cohort study.

BACKGROUND AND AIMS: Chronic atrophic gastritis (CAG) is a precancerous form of gastric cancer. However, with pathological diagnosis as the gold stand...

Ethical Design and Use of Robotic Care of the Elderly.

The Australian Royal Commission into Aged Care Quality and Safety acknowledged understaffing and substandard care in residential aged care and home ca...

TIMP-1: A Circulating Biomarker for Pulmonary Hypertension Diagnosis Among Chronic Obstructive Pulmonary Disease Patients.

Pulmonary hypertension (PH) is a common complication of chronic obstructive pulmonary disease (COPD) and induces increased mortality among COPD patien...

Detection and staging of chronic obstructive pulmonary disease using a computed tomography-based weakly supervised deep learning approach.

OBJECTIVES: Chronic obstructive pulmonary disease (COPD) is underdiagnosed globally. The present study aimed to develop weakly supervised deep learnin...

Identification of new putative inhibitors of 3-dehydroshikimate dehydratase from a combination of ligand- and structure-based and deep learning approaches.

The development of new drugs against is an essential strategy for fighting drug resistance. Although 3-dehydroquinate dehydratase (MtDHQ) is known to...

A Federated Mining Approach on Predicting Diabetes-Related Complications: Demonstration Using Real-World Clinical Data.

Chronic diabetes can lead to microvascular complications, including diabetic eye disease, diabetic kidney disease, and diabetic neuropathy. However, t...

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 (COPD), emphysema and airway wall remodeling. Thi...

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 evaluating radiographs, but published studies testing...

Mid-term functional outcomes of extraperitoneal robot-assisted simple prostatectomy: a single centre experience.

For large prostate volume, open simple prostatectomy (OSP) or holmium laser enucleation are the gold standard surgical treatment medical therapy failu...

A Machine-Learning Model for Lung Age Forecasting by Analyzing Exhalations.

Spirometers are important devices for following up patients with respiratory diseases. These are mainly located only at hospitals, with all the disadv...

Natural language processing for automated surveillance of intraoperative neuromonitoring in spine surgery.

We sought to develop natural language processing (NLP) methods for automated detection and characterization of neuromonitoring documentation from free...

Evaluation of Glucocorticoid Therapy in Asthma Children with Small Airway Obstruction Based on CT Features of Deep Learning.

This study was aimed at exploring the treatment of asthma children with small airway obstruction in CT imaging features of deep learning and glucocort...

The Normal Lung Index From Quantitative Computed Tomography for the Evaluation of Obstructive and Restrictive Lung Disease.

PURPOSE: Our objective was to evaluate whether the normal lung index (NLI) from quantitative computed tomography (QCT) analysis can be used to predict...

OnePetri: Accelerating Common Bacteriophage Petri Dish Assays with Computer Vision.

Bacteriophage plaque enumeration is a critical step in a wide array of protocols. The current gold standard for plaque enumeration on Petri dishes is...

Underdiagnosis bias of artificial intelligence algorithms applied to chest radiographs in under-served patient populations.

Artificial intelligence (AI) systems have increasingly achieved expert-level performance in medical imaging applications. However, there is growing co...