Allergy & Immunology

CoVEffect: interactive system for mining the effects of SARS-CoV-2 mutations and variants based on deep learning.

BACKGROUND: Literature about SARS-CoV-2 widely discusses the effects of variations that have spread ...

Determination of optimum intensity and duration of exercise based on the immune system response using a machine-learning model.

One of the important concerns in the field of exercise immunology is determining the appropriate int...

Deep learning to estimate lung disease mortality from chest radiographs.

Prevention and management of chronic lung diseases (asthma, lung cancer, etc.) are of great importan...

Utility of Allergen-Specific Patient-Directed Handouts Generated by Chat Generative Pretrained Transformer.

Large-scale electrophysiology and deep learning reveal distorted neural signal dynamics after hearing loss.

Listeners with hearing loss often struggle to understand speech in noise, even with a hearing aid. T...

Outcome-Supervised Deep Learning on Pathologic Whole Slide Images for Survival Prediction of Immunotherapy in Patients with Non-Small Cell Lung Cancer.

Although programmed death-(ligand) 1 (PD-(L)1) inhibitors are marked by durable efficacy in patients...

Natural language processing of pediatric progress notes for the identification of food allergy.

Novel machine learning method allerStat identifies statistically significant allergen-specific patterns in protein sequences.

Cutting-edge technologies such as genome editing and synthetic biology allow us to produce novel foo...

Science fact vs science fiction: A ChatGPT immunological review experiment gone awry.

Artificial intelligence (AI) has made great progress in recent years. The latest chatbot to make a s...

Current developments and perspectives in psoriasis.

The study of psoriasis has yielded fundamental new insights into immunologic regulation and innovati...

Synthetic biology, genetic circuits and machine learning: a new age of cancer therapy.

Synthetic biology has made it possible to rewire natural cellular responses to treat disease, notabl...

A decision support system based on artificial intelligence and systems biology for the simulation of pancreatic cancer patient status.

Oncology treatments require continuous individual adjustment based on the measurement of multiple cl...

Leveraging deep learning to improve vaccine design.

Deep learning has led to incredible breakthroughs in areas of research, from self-driving vehicles t...

Applications of deep learning to reduce the need for iodinated contrast media for CT imaging: a systematic review.

PURPOSE: The usage of iodinated contrast media (ICM) can improve the sensitivity and specificity of ...

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 d...

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 ca...

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 ...

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 en...

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 postoperativ...