Allergy & Immunology

Machine learning-based identification and characterization of mast cells in eosinophilic esophagitis.

BACKGROUND: Eosinophilic esophagitis (EoE) is diagnosed and monitored using esophageal eosinophil levels; however, EoE also exhibits a marked, understudied esophageal mastocytosis.

From pixels to patient care: deep learning-enabled pathomics signature offers precise outcome predictions for immunotherapy in esophageal squamous cell cancer.

BACKGROUND: Immunotherapy has significantly improved survival of esophageal squamous cell cancer (ESCC) patients, however the clinical benefit was limited to only a small portion of patients. This study aimed to perform a deep learning signature based on H&E-stained pathological specimens to accurately predict the clinical benefit of PD-1 inhibitors in ESCC patients.

An Accelerometer-Based Wearable Patch for Robust Respiratory Rate and Wheeze Detection Using Deep Learning.

Wheezing is a critical indicator of various respiratory conditions, including asthma and chronic obstructive pulmonary disease (COPD). Current diagnos...

A machine-learning exploration of the exposome from preconception in early childhood atopic eczema, rhinitis and wheeze development.

BACKGROUND: Most previous research on the environmental epidemiology of childhood atopic eczema, rhinitis and wheeze is limited in the scope of risk f...

Machine learning developed an intratumor heterogeneity signature for predicting prognosis and immunotherapy benefits in skin cutaneous melanoma.

Intratumor heterogeneity (ITH) is defined as differences in molecular and phenotypic profiles between different tumor cells and immune cells within a ...

Artificial intelligence in immunotherapy PET/SPECT imaging.

OBJECTIVE: Immunotherapy has dramatically altered the therapeutic landscape for oncology, but more research is needed to identify patients who are lik...

A Machine Learning Computational Framework Develops a Multiple Programmed Cell Death Index for Improving Clinical Outcomes in Bladder Cancer.

Comprehensive action patterns of programmed cell death (PCD) in bladder cancer (BLCA) have not yet been thoroughly investigated. Here, we collected 19...

Identification of Hit Compounds Using Artificial Intelligence for the Management of Allergic Diseases.

This study aimed to identify and evaluate drug candidates targeting the kinase inhibitory region of suppressor of cytokine signaling (SOCS) 3 for the ...

Preparing healthcare leaders of the digital age with an integrative artificial intelligence curriculum: a pilot study.

Artificial intelligence (AI) is rapidly being introduced into the clinical workflow of many specialties. Despite the need to train physicians who unde...

Harnessing artificial intelligence for analysing the impacts of nectar and pollen feeding in conservation biological control.

Plant-derived foods, such as nectar and pollen, have garnered substantial research attention due to their potential to support natural enemies of pest...

[Feeling analysis on allergen immunotherapy on using an unsupervised machine learning model].

OBJECTIVE: Analyze feelings about allergen-specific immunotherapy on using the VADER model VADER () model.

Machine learning based on blood test biomarkers predicts fast progression in advanced NSCLC patients treated with immunotherapy.

OBJECTIVE: Fast progression (FP) represents a desperate situation for advanced non-small cell lung cancer (NSCLC) patients undergoing immune checkpoin...

Demystification of artificial intelligence for respiratory clinicians managing patients with obstructive lung diseases.

INTRODUCTION: Asthma and chronic obstructive pulmonary disease (COPD) are leading causes of morbidity and mortality worldwide. Despite all available d...

Artificial Intelligence-Based 3D Printing Strategies for Bone Scaffold Fabrication and Its Application in Preclinical and Clinical Investigations.

3D printing has become increasingly popular in the field of bone tissue engineering. However, the mechanical properties, biocompatibility, and porosit...

Pathogenesis and precision medicine for predicting response in inflammatory bowel disease: advances and future directions.

The pathogenesis of inflammatory bowel disease (IBD) is complex and multifactorial. Undertreated disease has substantial individual and societal conse...

Predicting Penicillin Allergy: A United States Multicenter Retrospective Study.

BACKGROUND: Using the reaction history in logistic regression and machine learning (ML) models to predict penicillin allergy has been reported based o...

Hyperpolarized Gas Imaging in Lung Diseases: Functional and Artificial Intelligence Perspective.

Pathophysiologic changes in lung diseases are often accompanied by changes in ventilation and gas exchange. Comprehensive evaluation of lung function ...

A breast cancer-specific combinational QSAR model development using machine learning and deep learning approaches.

Breast cancer is the most prevalent and heterogeneous form of cancer affecting women worldwide. Various therapeutic strategies are in practice based o...

Proceedings from the inaugural Artificial Intelligence in Primary Immune Deficiencies (AIPID) conference.

Here, we summarize the proceedings of the inaugural Artificial Intelligence in Primary Immune Deficiencies conference, during which experts and advoca...

Perioperative Fluid and Vasopressor Therapy in 2050: From Experimental Medicine to Personalization Through Automation.

Intravenous (IV) fluids and vasopressor agents are key components of hemodynamic management. Since their introduction, their use in the perioperative ...