Pulmonology

Automated Assessment of OSCE Physical Exams using Multimodal AI

Background The assessment of physical examination skills in medical education is resource-intensive and prone to inter-rater variability. While artificial intelligence (AI) has successfully automated the grading of clinical notes and transcripts, evaluating the physical techniques themselves-what students do rather than what they say-remains an unsolved challenge. We evaluated whether a multimodal...

Visual question answering-based image-finding generation for pulmonary nodules on chest CT from structured annotations

Interpretation of imaging findings based on morphological characteristics is important for diagnosing pulmonary nodules on chest computed tomography (CT) images. In this study, we constructed a visual question answering (VQA) dataset from structured data in an open dataset and investigated an image-finding generation method for chest CT images, with the aim of enabling interactive diagnostic suppo...

Generation of Chest CT pulmonary Nodule Images by Latent Diffusion Models using the LIDC-IDRI Dataset

Recently, computer-aided diagnosis systems have been developed to support diagnosis, but their performance depends heavily on the quality and quantity...

SleePyPhases: A Workflow Framework for Sleep Data Harmonization, Analysis and Machine Learning

Data-driven sleep research relies on polysomnography data from various public repositories and vendor systems. Yet the lack of standardized access met...

Creating a scalable CT yield metric for pulmonary embolisms in the emergency department using an open-source large language model

BackgroundCT scans are the gold-standard diagnostic test for pulmonary embolisms (PE). Despite stable PE prevalence, CT use is rising in emergency dep...

Leveraging Explainable Temporal-Modelling Machine Learning to Identify Distinct Multimorbidity Trajectory Profiles in Acute Myocardial Infarction

IntroductionAcute myocardial infarction (AMI) remains a leading cause of mortality, with the coexistence of other conditions (i.e., multimorbidity) co...

VQ-Seg: Vector-Quantized Token Perturbation for Semi-Supervised Medical Image Segmentation

Consistency learning with feature perturbation is a widely used strategy in semi-supervised medical image segmentation. However, many existing perturb...

EvoMorph: Counterfactual Explanations for Continuous Time-Series Extrinsic Regression Applied to Photoplethysmography

Wearable devices enable continuous, population-scale monitoring of physiological signals, such as photoplethysmography (PPG), creating new opportuniti...

Handling Missing Modalities in Multimodal Survival Prediction for Non-Small Cell Lung Cancer

Accurate survival prediction in Non-Small Cell Lung Cancer (NSCLC) requires the integration of heterogeneous clinical, radiological, and histopatholog...

Exploring the Link Between Body Physiology and Cognition: The Role of the Brain and Ageing

Epidemiologists often report associations between cognitive functioning and bodily physiology in older adults, but the strength and drivers of this re...

High-dimensional spatial proteomics and novel machine learning pipeline identifies disease specific renal damage states

Lupus nephritis (LuN) and renal allograft rejection (RAR) manifest inflammation and fibrosis that ultimately lead to kidney failure. To quantitatively...

Histological aging signatures enable tissue-specific disease prediction from blood

Aging, the leading risk factor for numerous diseases, manifests through diverse structural and architectural changes in human tissues, providing an op...

Integrative Multi-Omics Analysis Reveals Novel Molecular Signatures, Disease Stratification and Therapeutic Opportunities in Primary Ciliary Dyskinesia: First AI-ML empowered platform towards precision medicine targeting human ciliopathies

Primary ciliary dyskinesia (PCD) belongs to the group of rare genetic disorders that is extremely hard to diagnose and treat. Current diagnostic modal...

Explainable Deep Learning for Pediatric Pneumonia Detection in Chest X-Ray Images

Background: Pneumonia remains a leading cause of morbidity and mortality among children worldwide, emphasizing the need for accurate and efficient dia...

Utilizing artificial intelligence and medical experts to identify predictors for common diagnoses in dyspneic adults: A cross-sectional study of consecutive emergency department patients from Southern Sweden.

OBJECTIVE: Half of all adult emergency department (ED) visits with a complaint of dyspnea involve acute heart failure (AHF), exacerbation of chronic o...

Machine learning driven prediction of drug efficacy in lung cancer: based on protein biomarkers and clinical features.

Currently, chemotherapy drugs are the first-line treatment for lung cancer patients, and evaluating their efficacy is of utmost significance. However,...

Decoding virulence and resistance in Klebsiella pneumoniae: Pharmacological insights, immunological dynamics, and in silico therapeutic strategies.

Klebsiella pneumoniae (K. pneumoniae) has become a serious global health concern due to its rising virulence and antibiotic resistance. As one of the ...

Machine learning-based approaches for distinguishing viral and bacterial pneumonia in paediatrics: A scoping review.

BACKGROUND AND OBJECTIVE: Pneumonia is the leading cause of hospitalisation and mortality among children under five, particularly in low-resource sett...

Application of Fourier transform infrared (FTIR) spectroscopy in liquid biopsy to predict the response to the first-line immunotherapy in non-small-cell lung cancer (NSCLC) patients.

The direction of anticancer therapies has changed in recent years, including the increasing use of immunotherapy. However, around 50 % of non-small-ce...

[Tongue swabs: a novel tool for tuberculosis screening].

Tuberculosis (TB) remains a significant global public health threat. Achieving the 2035 target for TB elimination requires interrupting its community ...