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...

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...

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...

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...

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

This article investigates optimal regulation scheme between tumor and immune cells based on the adap...

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 d...

Molecular MRI-Based Monitoring of Cancer Immunotherapy Treatment Response.

Immunotherapy constitutes a paradigm shift in cancer treatment. Its FDA approval for several indicat...

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 th...

Advances in artificial intelligence to predict cancer immunotherapy efficacy.

Tumor immunotherapy, particularly the use of immune checkpoint inhibitors, has yielded impressive cl...

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 i...

Ensemble deep learning enhanced with self-attention for predicting immunotherapeutic responses to cancers.

INTRODUCTION: Despite the many benefits immunotherapy has brought to patients with different cancers...

Development of an automated combined positive score prediction pipeline using artificial intelligence on multiplexed immunofluorescence images.

Immunotherapy targeting immune checkpoint proteins, such as programmed cell death ligand 1 (PD-L1), ...

Virtual Impactor-Based Label-Free Pollen Detection using Holography and Deep Learning.

Exposure to bio-aerosols such as pollen can lead to adverse health effects. There is a need for a po...

White blood cell detection, classification and analysis using phase imaging with computational specificity (PICS).

Treatment of blood smears with Wright's stain is one of the most helpful tools in detecting white bl...

Alternaria spore exposure in Bavaria, Germany, measured using artificial intelligence algorithms in a network of BAA500 automatic pollen monitors.

Although Alternaria spores are well-known allergenic fungal spores, automatic bioaerosol recognition...