COPD

Identification of diagnostic biomarkers and immune cell profiles associated with COPD integrated bioinformatics and machine learning.

This retrospective transcriptomic study leveraged bioinformatics and machine learning algorithms to identify novel gene biomarkers and explore immune cell infiltration profiles associated with chronic obstructive pulmonary disease (COPD). Utilizing an integrated analysis of metadata encompassing six gene expression omnibus (GEO) microarray datasets, 987 differentially expressed genes were identifi...

Towards reliable respiratory disease diagnosis based on cough sounds and vision transformers

Recent advancements in deep learning techniques have sparked performance boosts in various real-world applications including disease diagnosis based on multi-modal medical data. Cough sound data-based respiratory disease (e.g., COVID-19 and Chronic Obstructive Pulmonary Disease) diagnosis has also attracted much attention. However, existing works usually utilise traditional machine learning or d...

AcousAF: Acoustic Sensing-Based Atrial Fibrillation Detection System for Mobile Phones

Atrial fibrillation (AF) is characterized by irregular electrical impulses originating in the atria, which can lead to severe complications and even...

Can Rule-Based Insights Enhance LLMs for Radiology Report Classification? Introducing the RadPrompt Methodology

Developing imaging models capable of detecting pathologies from chest X-rays can be cost and time-prohibitive for large datasets as it requires supe...

Examining the effectiveness of artificial intelligence applications in asthma and COPD outpatient support in terms of patient health and public cost: SWOT analysis.

This research aimed to examine the effectiveness of artificial intelligence applications in asthma and chronic obstructive pulmonary disease (COPD) ou...

Towards Personalized Inhalation Therapy by Correlating Chest CT Imaging and Pulmonary Function Test Features Using Machine Learning.

Inhalation therapy is the predominant method of treatment for a variety of respiratory diseases. The effectiveness of such treatment is dependent on t...

Audio Cough Analysis by Parametric Modelling of Weighted Spectrograms to Interpret the Output of Convolutional Neural Networks.

This study explores the feasibility of employing eXplainable Artificial Intelligence (XAI) methodologies for the analysis of cough patterns in respira...

Deep Learning to Predict Glaucoma Progression using Structural Changes in the Eye

Glaucoma is a chronic eye disease characterized by optic neuropathy, leading to irreversible vision loss. It progresses gradually, often remaining u...

Ethical considerations for artificial intelligence in dermatology: a scoping review.

The field of dermatology is experiencing the rapid deployment of artificial intelligence (AI), from mobile applications (apps) for skin cancer detecti...

Deep Learning-Based Kernel Adaptation Enhances Quantification of Emphysema on Low-Dose Chest CT for Predicting Long-Term Mortality.

OBJECTIVES: The aim of this study was to ascertain the predictive value of quantifying emphysema using low-dose computed tomography (LDCT) post deep l...

An intentional approach to managing bias in general purpose embedding models.

Advances in machine learning for health care have brought concerns about bias from the research community; specifically, the introduction, perpetuatio...

A framework for language technologies in behavioral research and clinical applications: Ethical challenges, implications, and solutions.

Technological advances in the assessment and understanding of speech and language within the domains of automatic speech recognition, natural language...

Assessment of Osteoprotegerin and Receptor Activator of Nf-Κb Ligand in Malaysian Male Patients with Chronic Obstructive Pulmonary Disease: A Cross-Sectional Study.

Background: Limited information exists regarding the pathophysiological interactions between osteoporosis and chronic obstructive pulmonary disease (C...

[Advances in chest imaging in early chronic obstructive pulmonary disease].

Chronic obstructive pulmonary disease(COPD)is a heterogeneous and complex disease, and is characterized by exertional dyspnea and chronic cough. For m...

Machine learning and deep learning predictive models for long-term prognosis in patients with chronic obstructive pulmonary disease: a systematic review and meta-analysis.

BACKGROUND: Machine learning and deep learning models have been increasingly used to predict long-term disease progression in patients with chronic ob...

[Gentle Method to Elevate Left Liver Lobe in Robot Assisted Gastrectomy].

Robot-assisted gastrectomy with the Davinci XiTM has been performed in our department since August 2019. This technique requires elevation of the left...

Research on Pectoral Muscle Segmentation Algorithm of CT Image Based on Deep Learning.

Chronic obstructive pulmonary disease (COPD) is a common respiratory disease, which seriously endangers human health and is also one of the important ...

Deep Learning Assessment of Progression of Emphysema and Fibrotic Interstitial Lung Abnormality.

Although studies have evaluated emphysema and fibrotic interstitial lung abnormality individually, less is known about their combined progression. T...

The Promise of Quantitative Computed Tomographic Analysis in Assessing Progression of Interstitial Lung Abnormalities and Emphysema in Smokers.

Assessing Human-Human Kinematics for the Implementation of Robot-Assisted Physical Therapy in Humanoids: A Pilot Study.

The development of humanoids with bimanual manipulator arms may facilitate assistive robots to perform physical therapy with older adults living at ho...