Pulmonology

Latest AI and machine learning research in pulmonology for healthcare professionals.

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Transformer-based multiclass segmentation pipeline for basic kidney histology

Multiclass segmentation of microanatomy in kidney biopsies is an important and non-trivial task in computational renal pathology. In a multicenter study, we densely annotated basic anatomical objects (glomeruli, tubules, and vessels) in 261 regions of interest of 147 kidney biopsy WSIs sourced from the archives of hospitals in Amsterdam, Utrecht, and Leiden (Netherlands). And we trained multiple U...

Open-source computational pipeline automatically flags instances of acute respiratory distress syndrome from electronic health records

Physicians, particularly intensivists, face information overload and decision fatigue, underscoring the need for automated diagnostic tools. Acute Respiratory Distress Syndrome (ARDS) affects over 10% of critical care patients, with over 40% mortality rate, yet is only recognized in 30-70% of cases in clinical settings. We present a reproducible computational pipeline that automates ARDS adjudicat...

The epidemiology of pathogens with pandemic potential: A review of key parameters and clustering analysis

In the light of the COVID-19 pandemic many countries are trying to widen their pandemic planning from its traditional focus on influenza. However, it ...

Revolutionizing COPD and Asthma Management with Artificial Intelligence

The integration of artificial intelligence (AI) into the management of chronic obstructive pulmonary disease (COPD) and asthma offers significant adva...

Image-based Mandibular and Maxillary Parcellation and Annotation using Computer Tomography (IMPACT): A Deep Learning-based Clinical Tool for Orodental Dose Estimation and Osteoradionecrosis Assessment

Accurate delineation of orodental structures on radiotherapy CT images is essential for dosimetric assessments and dental decisions. We propose a deep...

A Deep Learning Framework for Causal Inference in Clinical Trial Design: The CURE AI Large Clinicogenomic Foundation Model

Clinical research is limited by the capability to define the most important combinations of clinical features and biomarkers that predict therapeutic ...

Profile of deaths mentioning ischemic and hemorrhagic stroke in Brazil: a population-based machine learning analysis

Brazil has the highest stroke rates in Latin America. The aim of this study was to investigate the profile of deaths mentioning stroke in Brazil betwe...

Predicting community-acquired pneumonia outcome using time series data and machine learning

Community-acquired pneumonia (CAP) is an acute respiratory condition associated with high mortality in adult populations and is potentially more serio...

Suitability of just-in-time adaptive intervention in post-COVID-19-related symptoms: A systematic scoping review

Patients with post-COVID-19-related symptoms require active and timely support in self-management. Just-in-time adaptive interventions (JITAI) seem pr...

Comprehensive Evaluation of Human Donor Liver Viability with Polarization-Sensitive Optical Coherence Tomography

Human liver transplantation is severely constrained by a critical shortage of donor livers, with approximately one quarter of patients on the waiting ...

In silico perturbations provide multivariate interpretability in predicting post-lung transplant outcomes

Lung transplantation is a life-saving therapy for end-stage lung disease but has the poorest survival among solid organ transplants. We analyzed stand...

RiskAgent: Autonomous Medical AI Copilot for Generalist Risk Prediction

The application of Large Language Models (LLMs) to various clinical applications has attracted growing research attention. LLMs currently achieve comp...

Automated diagnosis of usual interstitial pneumonia on chest CT via the mean curvature of isophotes

To test whether the mean curvature of isophotes (MCI), a geometric image transformation, can be used to improve automatic detection on chest CT of Usu...

A multivariate cell-based assay for blood-based diagnostics enhances lung cancer risk stratification

The indicator cell assay platform (iCAP) is a tool for blood-based diagnostics that addresses the low signal-to-noise ratio of blood biomarkers by usi...

Radiomics-Based Lung Nodule Classification with Stacking Ensembles

Radiomics, an emerging field in medical imaging, leverages advanced mathematical analysis to extract quantitative metrics from medical images, aiding ...

AI-Driven and Automated Continuous Oxygen Saturation Monitoring and LTOT: A Systematic Review

Long-term oxygen therapy (LTOT) is essential for patients with chronic hypoxemia, particularly due to chronic obstructive pulmonary disease (COPD). Ho...

Pulmonary tuberculosis prediction using CAD4TB artificial intelligence (computer-aided detection for tuberculosis) based on thoracic x-ray photos among Indonesian subjects in hospital

Tuberculosis remains a major global health concern, particularly in high-burden countries where early detection is essential but often limited by insu...

Understanding the Feasibility of Computer Vision in Diagnosing Respiratory Infections in Pediatric Emergency Rooms

Respiratory infections are a leading cause of pediatric emergency visits globally, requiring timely and accurate assessment. This study evaluated the ...

Scalable Identification of Clinically Relevant COPD Documents: A Lightweight NLP Model for Large-Scale EHR Datasets

The widespread adoption of electronic health records (EHRs) has resulted in the generation of large volumes of clinical notes. Learning algorithms and...

Feasibility of Machine Learning Analysis for the Identification of Patients with Possible Primary Ciliary Dyskinesia

Significant diagnostic delays are common in primary ciliary dyskinesia (PCD), a rare disease that is significantly underdiagnosed. Scalable screening ...

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