Allergy & Immunology

Deep Learning-Based Stratification of Gastric Cancer Patients from Hematoxylin and Eosin-Stained Whole Slide Images by Predicting Molecular Features for Immunotherapy Response.

Determining the molecular characteristics of cancer patients is crucial for optimal immunotherapy decisions. The aim of this study was to screen immunotherapy beneficiaries by predicting key molecular features from hematoxylin and eosin-stained images based on deep learning models. An independent data set from Asian gastric cancer patients was included for external validation. In addition, a segme...

Large-Scale Modeling of Sparse Protein Kinase Activity Data.

Protein kinases are a protein family that plays an important role in several complex diseases such as cancer and cardiovascular and immunological diseases. Protein kinases have conserved ATP binding sites, which when targeted can lead to similar activities of inhibitors against different kinases. This can be exploited to create multitarget drugs. On the other hand, selectivity (lack of similar act...

Artificial Intelligence Chatbots in Allergy and Immunology Practice: Where Have We Been and Where Are We Going?

Artificial intelligence (AI) is rapidly becoming a valuable tool in healthcare, providing clinicians with a new AI lens perspective for patient care, ...

Home monitoring with connected mobile devices for asthma attack prediction with machine learning.

Monitoring asthma is essential for self-management. However, traditional monitoring methods require high levels of active engagement, and some patient...

Biologically Interpretable Deep Learning To Predict Response to Immunotherapy In Advanced Melanoma Using Mutations and Copy Number Variations.

Only 30-40% of advanced melanoma patients respond effectively to immunotherapy in clinical practice, so it is necessary to accurately identify the res...

The artificial intelligence and machine learning in lung cancer immunotherapy.

Since the past decades, more lung cancer patients have been experiencing lasting benefits from immunotherapy. It is imperative to accurately and intel...

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 in the past 3 years. Such information is dispersed...

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 intensity and duration of exercise to prevent suppres...

Deep learning to estimate lung disease mortality from chest radiographs.

Prevention and management of chronic lung diseases (asthma, lung cancer, etc.) are of great importance. While tests are available for reliable diagnos...

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. To better understand the auditory processing defici...

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 with non-small cell lung cancer (NSCLC), approxim...

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 foods and functional proteins. However, their toxicit...

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 splash is ChatGPT. To see if this type of AI could ...

Current developments and perspectives in psoriasis.

The study of psoriasis has yielded fundamental new insights into immunologic regulation and innovative therapies in a way that few other diseases have...

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, notably demonstrated by chimeric antigen receptor (CAR) ...

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 clinical parameters. Prediction tools exploiting the...

Leveraging deep learning to improve vaccine design.

Deep learning has led to incredible breakthroughs in areas of research, from self-driving vehicles to solutions, to formal mathematical proofs. In the...

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 computed tomography (CT) for many clinical indicat...