COPD

Developing artificial intelligence tools for institutional review board pre-review: A pilot study on ChatGPT’s accuracy and reproducibility

This pilot study is the first phase of a broader project aimed at developing an explainable artificial intelligence (AI) tool to support the ethical evaluation of Japanese-language clinical research documents. The tool is explicitly not intended to assist document drafting. We assessed the baseline performance of generative AI—Generative Pre-trained Transformer (GPT)-4 and GPT-4o—in analyzing clin...

Development of Computational Pipeline for Right Ventricular Hemodynamic Single-Beat Analysis

Load-independent indices of right ventricular (RV) dysfunction aid in the prognosis of patients with pulmonary hypertension (PH), but their acquisition remains difficult. This study aimed to develop a novel computer vision artificial intelligence-based pipeline that can estimate load-independent RV functional indices using screenshots of the RV pressure-time waveform from a standard clinical right...

Machine Learning Analysis of Electronic Health Records Identifies Interstitial Lung Disease and Predicts Mortality in Patients with Systemic Sclerosis

Interstitial lung disease (ILD) is the leading cause of death in patients with systemic sclerosis (SSc), affecting more than 40% of this population. D...

CLINICAL VALIDATION OF SWAASA ARTIFICIAL INTELLIGENCE PLATFORM USING COUGH SOUNDS FOR SCREENING AND DIAGNOSIS OF RESPIRATORY DISEASES

Analysis of cough sounds have the potential to give a clue regarding the underlying respiratory disease. The Swaasa AI platform using artificial intel...

Light Convolutional Neural Network to Detect Chronic Obstructive Pulmonary Disease (COPDxNet): A Multicenter Model Development and External Validation Study

Approximately 70% of adults with chronic obstructive pulmonary disease (COPD) remain undiagnosed. Opportunistic screening using chest computed tomogra...

Spirometry parameter prediction using Acoustic characteristics of Cough

Spirometry evaluates lung function by measuring airflow post-maximal inspiration, using parameters like FEV1, FVC, and the FEV1/FVC ratio for respirat...

Epigenetic patient stratification reveals a sub-endotype of type 2 asthma with altered B-cell response

Despite biomarker-guided treatment strategies, clinical outcomes among patients with type 2 (T2)-high asthma remain heterogeneous, with some patients ...

Chronic Obstructive Pulmonary Disease Prediction Using Deep Convolutional Network

Artificial intelligence and deep learning are increasingly applied in the clinical domain, particularly for early and accurate disease detection using...

Using Hourly Aggregated Respiratory Rate and Expiratory Time with Machine Learning to Identify Remote COPD Exacerbations

Exacerbations of chronic obstructive pulmonary disease (COPD) are a major cause of morbidity and mortality. Various models for identifying exacerbatio...

Improving Surrogate Endpoints for Survival Prediction Through Integration of Patient-Reported Outcomes

Overall survival (OS) remains the gold standard for oncology drug approval, but measuring it requires long follow-up and is impractical in certain onc...

Multi-branch convolutional neural network using intracranial EEG high frequency oscillation features for predicting post-surgical seizure outcomes

Pathological high-frequency oscillations (HFOs 80-600 Hz) in intracranial EEG distinguish epileptogenic cortex. However, it is uncertain whether utili...

Wearable Sleep Measures May Improve Machine Learning Prediction of Home-based Pulmonary Rehabilitation Engagement Among Patients With Chronic Obstructive Pulmonary Disease: A Proof-of-Concept Study

To evaluate whether incorporating baseline sleep measures from a wrist-worn activity monitor in machine learning (ML) models improved the prediction o...

3DeepVOG: An Open-Source Framework for Real-Time, Accurate 3D Gaze Tracking with Deep Learning

Eye movements are key biomarkers for diagnosing and monitoring neuro-otological, neuro-ophthalmological and neurodegenerative disorders. Video-oculogr...

A Zero-Burden Sleep Foundation Model Built on Cardiorespiratory Signals from 800,000+ Hours of Multi-Ethnic Sleep Recordings

Sleep disorders pose a major global health burden and are associated with a wide range of adverse health outcomes. Polysomnography (PSG) is the gold s...

Prognostic role of COVID-19 pneumonia signs and other CT-biomarkers for survival in patients with malignant neoplasms: the ARILUS project

Clinically manifested pneumonia associated with COVID-19 infection in cancer patients has been associated with worse prognosis. The prognostic signifi...

Development and evaluation of a multivariate prediction model for diagnosing asthma in patients with clinically suspected asthma using capnography

Diagnosis of asthma in primary care is challenged by a multistep pathway with variable adherence leading to significant misdiagnosis, late diagnosis a...

Computational Review of Technology-Assisted Medical Evidence Synthesis through Human-LLM Collaboration: A Case Study of Cochrane

Medical evidence synthesis, typically done by systematic reviews, requires extensive manual effort across stages such as searching, screening, extract...

The Association Between Oral Microbiota and Chronic Obstructive Pulmonary Disease: An Integrated Study of Genetic Causal Inference and Bioinformatics Analysis

Chronic obstructive pulmonary disease (COPD) is the third leading cause of global mortality. Emerging evidence suggests the oral microbiome may contri...

Artificial intelligence-driven ECG biomarkers for screening of large pericardial effusion

Pericardial effusion can progress to life-threatening cardiac tamponade when large or rapidly accumulating, yet early diagnosis is frequently delayed ...

A Comparison of Two Deep Learning Approaches to Distinguish Functional Dissociative from Epileptic Seizures Using Event Videos

Differentiating between motor functional dissociative seizures (FDS) and motor epileptic seizures (ES) is a common diagnostic challenge, requiring vid...