Allergy & Immunology

Demonstration of Convolutional Neural Networks to Determine Patch Test Reactivity.

Convolutional neural networks (CNNs) have the potential to assist allergists and dermatologists in ...

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 wor...

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. P...

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 t...

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) algorithm...

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 in...

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 medi...

De novo drug design based on patient gene expression profiles via deep learning.

Computational de novo drug design is a challenging issue in medicine, and it is desirable to conside...

Current state and prospects of artificial intelligence in allergy.

The field of medicine is witnessing an exponential growth of interest in artificial intelligence (AI...

The seductive allure of spatial biology: accelerating new discoveries in the life sciences.

Spatial biology is a rapidly developing field which enables the visualization of protein and transcr...

Tumor microenvironment-based signatures distinguish intratumoral heterogeneity, prognosis, and immunogenomic features of clear cell renal cell carcinoma.

BACKGROUND: The tumor microenvironment (TME) performs a crucial function in the tumorigenesis and re...

Allergic to ChatGPT? Introducing a Desensitization Protocol to Embrace Artificial Intelligence.

Identifying the active ingredients of carbonized Typhae Pollen by spectrum-effect relationship combined with MBPLS, PLS, and SVM algorithms.

Typhae Pollen (TP) and its carbonized product (carbonized Typhae Pollen, CTP), as cut-and-dried herb...

Computational Methods in Immunology and Vaccinology: Design and Development of Antibodies and Immunogens.

The design of new biomolecules able to harness immune mechanisms for the treatment of diseases is a ...

Cuproptosis facilitates immune activation but promotes immune escape, and a machine learning-based cuproptosis-related signature is identified for predicting prognosis and immunotherapy response of gliomas.

AIMS: Cell death, except for cuproptosis, in gliomas has been extensively studied, providing novel t...

Machine-learning and combined analysis of single-cell and bulk-RNA sequencing identified a DC gene signature to predict prognosis and immunotherapy response for patients with lung adenocarcinoma.

BACKGROUND: Innate immune effectors, dendritic cells (DCs), influence cancer prognosis and immunothe...

Screening of the shared pathogenic genes of ulcerative colitis and colorectal cancer by integrated bioinformatics analysis.

Ulcerative colitis (UC) is one of the high-risk pathogenic factors for colorectal cancer (CRC). Howe...

Topological deep learning based deep mutational scanning.

High-throughput deep mutational scanning (DMS) experiments have significantly impacted protein engin...

Immunodiagnosis - the promise of personalized immunotherapy.

Immunotherapy showed remarkable efficacy in several cancer types. However, the majority of patients ...

A Survey on Artificial Intelligence in Pulmonary Imaging.

Over the last decade, deep learning (DL) has contributed a paradigm shift in computer vision and ima...

Cancer immunotherapy response prediction from multi-modal clinical and image data using semi-supervised deep learning.

BACKGROUND AND PURPOSE: Immunotherapy is a standard treatment for many tumor types. However, only a ...