Atopy

Activation status of immune cells in the airway is a defining feature of severe fungal asthma

Airborne fungi are potent inducers of respiratory disease and cause the debilitating conditions severe asthma with fungal sensitisation (SAFS) and allergic bronchopulmonary aspergillosis (ABPA). However, the immune cell types and the inflammatory airway environment that defines SAFS and ABPA patients is not extensively characterised. To address this, we recruited SAFS and ABPA patients, asthmatics...

ROC Analysis of Biomarker Combinations in Fragile X Syndrome-Specific Clinical Trials: Evaluating Treatment Efficacy via Exploratory Biomarkers

Fragile X Syndrome (FXS) is a rare neurodevelopmental disorder caused by a trinucleotide repeat expansion on the 5’ untranslated region of the FMR1 gene. FXS is characterized by intellectual disability, anxiety, sensory hypersensitivity, and difficulties with executive function. A recent phase 2 placebo-controlled clinical trial assessing BPN14770, a first-in-class phosphodiesterase 4D allosteric ...

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...

Identifying Key Predictive Features for Opioid Use Disorder Using Machine Learning

Opioid Use Disorder (OUD) continues to pose a pressing public health challenge across the United States, highlighting the critical need for early and ...

Machine Learning-Based Reconstruction of 2D MRI for Quantitative Morphometry in Epilepsy

Structural neuroimaging analyses require ‘research quality’ images, acquired with costly MRI acquisitions. Isotropic (3D-T1) images are desirable for ...

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 ...

How do clinician and parent reported data differ? An analysis of similarity and difference in the datasets from a cross-syndrome genetics cohort study(GenROC)

Parent/patient-reported datasets provide ready access to phenotypic data for monogenic neurodevelopmental disorders yet their concordance with clinica...

Scaling genetic discovery for organ volumes using machine learning-assisted imputation and bias-corrected GWAS

MRI-derived organ and tissue volumes are powerful endophenotypes for studying complex disease, but their availability is limited by cost and throughpu...

The Cleaning Simulation: Applying Predictive Decision Trees for Chemical Exposure Risks and Asthma-Like Symptoms in Laboratory Workers

Exposure to chemical irritants in laboratory and medical environments poses significant health risks to workers, particularly in relation to asthma-li...

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...

Non-invasive epidermal proteomics and machine learning permits molecular subclassification of psoriasis and eczematous dermatitis

Current approaches to selecting molecularly targeted therapies (biologics and oral small molecules) for immune-mediated skin diseases largely overlook...

Comparative Benchmarking of Five Contemporary Language Models on Clinical Reasoning

The rapid integration of Large Language Models (LLMs) into healthcare raises critical questions regarding their safety and reliability. While models o...

Demographics, Overlap, and Latency of Severe Cutaneous Adverse Reactions in an FDA Database

Severe cutaneous adverse reactions (SCARs), including Stevens-Johnson syndrome/toxic epidermal necrolysis (SJS-TEN), drug reaction with eosinophilia a...

Identification of potential diagnostic markers and molecular mechanisms of asthma and ulcerative colitis based on bioinformatics and machine learning.

BACKGROUNDS: Asthma and ulcerative colitis (UC) are chronic inflammatory diseases linked through the "gut-lung axis," but their shared mechanisms rema...

Home spirometry telemonitoring in pediatric patients with asthma: a mixed study.

BACKGROUND: To evaluate the feasibility and practicality of home spirometry telemonitoring for pediatric patients with asthma, including both motivato...

Deciphering mitochondrial dysfunction in keratoconus: Insights into ACSL4 from machine learning-based bulk and single-cell transcriptome analyses and experimental validation.

Keratoconus (KC) is a prevalent ectatic corneal disease and the leading cause of corneal transplantation globally. Despite evidence of mitochondrial a...

A Comparative Study on Machine Learning Models to Classify Diseases Based on Patient Behaviour and Habits

In recent years, ML algorithms have been shown to be useful for predicting diseases based on health data and posed a potential application area for ...

Feature engineering vs. deep learning for paper section identification: Toward applications in Chinese medical literature

Section identification is an important task for library science, especially knowledge management. Identifying the sections of a paper would help fil...

Personalized and Safe Route Planning for Asthma Patients Using Real-Time Environmental Data

Asthmatic patients are very frequently affected by the quality of air, climatic conditions, and traffic density during outdoor activities. Most of t...

"Oh, sh*t! I actually opened the document!": An Empirical Study of the Experiences with Suspicious Emails in Virtual Reality Headsets

This paper reports on a study exploring user experiences with suspicious emails and associated warnings when accessed through virtual reality (VR) h...