Allergy & Immunology

A Novel Machine-Learning Framework Based on a Hierarchy of Dispute Models for the Identification of Fish Species Using Multi-Mode Spectroscopy.

Seafood mislabeling rates of approximately 20% have been reported globally. Traditional methods for fish species identification, such as DNA analysis and polymerase chain reaction (PCR), are expensive and time-consuming, and require skilled technicians and specialized equipment. The combination of spectroscopy and machine learning presents a promising approach to overcome these challenges. In our ...

Risk of sexual transmission of HIV in the context of viral load suppression.

BACKGROUND: In 2018, the Public Health Agency of Canada (PHAC) published a systematic review to calculate the risk of sexual transmission of human immunodeficiency virus (HIV) in the context of antiretroviral therapy (ART). In 2022, PHAC commissioned the Canadian Agency for Drugs and Technologies in Health (CADTH) to conduct a rapid review of evidence published since 2017. We undertook a meta-anal...

Reducing Gadolinium Contrast With Artificial Intelligence.

Gadolinium contrast is an important agent in magnetic resonance imaging (MRI), particularly in neuroimaging where it can help identify blood-brain bar...

Untargeted metabolomic profiling in children identifies novel pathways in asthma and atopy.

BACKGROUND: Asthma and other atopic disorders can present with varying clinical phenotypes marked by differential metabolomic manifestations and enric...

The water-soluble subfraction from Artemisia argyi alleviates LPS-induced inflammatory responses via multiple pathways and targets in vitro and in vivo.

ETHNOPHARMACOLOGICAL RELEVANCE: As a traditional Chinese medicine, Artemisia argyi has been used medicinally and eaten for more than 2000 years in Chi...

Artificial Intelligence Chatbot Shows Multiple Inaccuracies When Responding to Questions About Eosinophilic Esophagitis.

Reply to Dages et al: You AIn't using it right-artificial intelligence progress in allergy.

Anaphylactic Shock to Intravenous Indocyanine Green During a Robotic Right Colectomy.

Intravenous indocyanine green (IV ICG) is regarded as a safe immunofluorescence agent used to assess bowel perfusion prior to creating bowel anastomos...

ChatGPT's performance in dentistry and allergyimmunology assessments: a comparative study.

Large language models (LLMs) such as ChatGPT have potential applications in healthcare, including dentistry. Priming, the practice of providing LLMs w...

Predicting the therapeutic efficacy of AIT for asthma using clinical characteristics, serum allergen detection metrics, and machine learning techniques.

Bronchial asthma is a prevalent non-communicable disease among children. The study collected clinical data from 390 children aged 4-17 years with asth...

Unraveling the link between PTBP1 and severe asthma through machine learning and association rule mining method.

Severe asthma is a chronic inflammatory airway disease with great therapeutic challenges. Understanding the genetic and molecular mechanisms of severe...

The spatial distribution of interleukin-4 (IL-4) reference values in China based on a back propagation (BP) neural network.

This study aimed to investigate the geospatial distribution of normal reference values of Interleukin 4 (IL-4) in healthy Chinese adults and to provid...

A robust deep learning workflow to predict CD8 + T-cell epitopes.

BACKGROUND: T-cells play a crucial role in the adaptive immune system by triggering responses against cancer cells and pathogens, while maintaining to...

Demonstration of Convolutional Neural Networks to Determine Patch Test Reactivity.

Convolutional neural networks (CNNs) have the potential to assist allergists and dermatologists in the analysis of patch tests. Such models can help ...

COVID-19 diagnosis using clinical markers and multiple explainable artificial intelligence approaches: A case study from Ecuador.

The COVID-19 pandemic erupted at the beginning of 2020 and proved fatal, causing many casualties worldwide. Immediate and precise screening of affecte...

Deductive automated pollen classification in environmental samples via exploratory deep learning and imaging flow cytometry.

Pollen and tracheophyte spores are ubiquitous environmental indicators at local and global scales. Palynology is typically performed manually by micro...

Deep learning-based pectoralis muscle volume segmentation method from chest computed tomography image using sagittal range detection and axial slice-based segmentation.

The pectoralis muscle is an important indicator of respiratory muscle function and has been linked to various parenchymal biomarkers, such as airflow ...

Groundwork for AI: Enforcing a benchmark for neoantigen prediction in personalized cancer immunotherapy.

This article expands on recent studies of machine learning or artificial intelligence (AI) algorithms that crucially depend on benchmark datasets, oft...

Small immunological clocks identified by deep learning and gradient boosting.

BACKGROUND: The aging process affects all systems of the human body, and the observed increase in inflammatory components affecting the immune system ...

Biology-guided deep learning predicts prognosis and cancer immunotherapy response.

Substantial progress has been made in using deep learning for cancer detection and diagnosis in medical images. Yet, there is limited success on predi...