Allergy & Immunology

Deep learning for detection of drug hypersensitivity reactions.

MEMMAL: A tool for expanding large-scale mechanistic models with machine learned associations and big datasets.

Computational models that can explain and predict complex sub-cellular, cellular, and tissue-level drug response mechanisms could speed drug discovery and prioritize patient-specific treatments (i.e., precision medicine). Some models are mechanistic with detailed equations describing known (or supposed) physicochemical processes, while some are statistical or machine learning-based approaches, tha...

Artificial intelligence in cancer immunotherapy: Applications in neoantigen recognition, antibody design and immunotherapy response prediction.

Cancer immunotherapy is a method of controlling and eliminating tumors by reactivating the body's cancer-immunity cycle and restoring its antitumor im...

Can You Picture It? Using Smartphone Artificial Intelligence to Identify Allergenic Plants.

Explainable AI for unveiling deep learning pollen classification model based on fusion of scattered light patterns and fluorescence spectroscopy.

Pollen monitoring have become data-intensive in recent years as real-time detectors are deployed to classify airborne pollen grains. Machine learning ...

Quantifying Inflammatory Response and Drug-Aided Resolution in an Atopic Dermatitis Model with Deep Learning.

Noninvasive quantification of dermal diseases aids efficacy studies and paves the way for broader enrollment in clinical studies across varied demogra...

Artificial intelligence and the potential for perioperative delabeling of penicillin allergies for neurosurgery inpatients.

PURPOSE OF THE ARTICLE: Patients with penicillin allergy labels are more likely to have postoperative wound infections. When penicillin allergy labels...

Neural-Network-Based Immune Optimization Regulation Using Adaptive Dynamic Programming.

This article investigates optimal regulation scheme between tumor and immune cells based on the adaptive dynamic programming (ADP) approach. The thera...

Automatic real-time monitoring of fungal spores: the case of spp.

We present the first implementation of the monitoring of airborne fungal spores in real-time using digital holography. To obtain observations of spp....

Molecular MRI-Based Monitoring of Cancer Immunotherapy Treatment Response.

Immunotherapy constitutes a paradigm shift in cancer treatment. Its FDA approval for several indications has yielded improved prognosis for cases wher...

DapNet-HLA: Adaptive dual-attention mechanism network based on deep learning to predict non-classical HLA binding sites.

Human leukocyte antigen (HLA) plays a vital role in immunomodulatory function. Studies have shown that immunotherapy based on non-classical HLA has es...

Deep learning-assisted ultra-accurate smartphone testing of paper-based colorimetric ELISA assays.

Smartphone has long been considered as one excellent platform for disease screening and diagnosis, especially when combined with microfluidic paper-ba...

Imaging-derived biomarkers in Asthma: Current status and future perspectives.

Asthma is a common disorder affecting around 315 million individuals worldwide. The heterogeneity of asthma is becoming increasingly important in the ...

A Deep Learning Approach to Visualize Aortic Aneurysm Morphology Without the Use of Intravenous Contrast Agents.

BACKGROUND: Intravenous contrast agents are routinely used in CT imaging to enable the visualization of intravascular pathology, such as with abdomina...

Advances in artificial intelligence to predict cancer immunotherapy efficacy.

Tumor immunotherapy, particularly the use of immune checkpoint inhibitors, has yielded impressive clinical benefits. Therefore, it is critical to accu...

Rapid simultaneous analysis of anti human immunodeficiency virus drugs in pharmaceutical formulation by smart spectrophotometry based on multivariate calibration and least squares support vector machine methods.

In this study, two chemometrics methods, including partial least squares regression (PLS) and least squares support vector machine (LS-SVM) were appli...

Molecular modeling of C1-inhibitor as SARS-CoV-2 target identified from the immune signatures of multiple tissues: An integrated bioinformatics study.

The expeditious transmission of the severe acute respiratory coronavirus 2 (SARS-CoV-2), a strain of COVID-19, crumbled the global economic strength a...

Predicting Antigenic Distance from Genetic Data for PRRSV-Type 1: Applications of Machine Learning.

The control of porcine reproductive and respiratory syndrome (PRRS) remains a significant challenge due to the genetic and antigenic variability of th...

Children's views on artificial intelligence and digital twins for the daily management of their asthma: a mixed-method study.

New technologies enable the creation of digital twin systems (DTS) combining continuous data collection from children's home and artificial intelligen...

Plasma cell subtypes analyzed using artificial intelligence algorithm for predicting biochemical recurrence, immune escape potential, and immunotherapy response of prostate cancer.

BACKGROUND: Plasma cells as an important component of immune microenvironment plays a crucial role in immune escape and are closely related to immune ...