Allergy

Artificial intelligence in the diagnosis of pediatric allergic diseases.

Artificial intelligence (AI) is a field of data science pertaining to advanced computing machines capable of learning from data and interacting with the human world. Early diagnosis and diagnostics, self-care, prevention and wellness, clinical decision support, care delivery, and chronic care management have been identified within the healthcare areas that could benefit from introducing AI. In ped...

The Protein Level and Molecular Weight Analysis in Different Children's Toothpaste, which Probably Induced Hypersensitivity.

CONTEXT: A new case of an allergic reaction due to the use of toothpaste was found in California, United States, causing the death of an 11-year-old girl. Ingredients contained in toothpaste suspected as a cause of allergies are milk protein compounds.

Efficacy predictors of omalizumab in Chinese patients with moderate-to-severe allergic asthma: Findings from a analysis of a randomised phase III study.

BACKGROUND: Omalizumab has demonstrated efficacy as an add-on therapy in Chinese patients with moderate-to-severe allergic asthma. This analysis asse...

The RoScan Thermal 3D Body Scanning System: Medical Applicability and Benefits for Unobtrusive Sensing and Objective Diagnosis.

The RoScan is a novel, high-accuracy multispectral surface scanning system producing colored 3D models that include a thermal layer. (1) Background: a...

Development and Validation of a Deep Learning Model for Detection of Allergic Reactions Using Safety Event Reports Across Hospitals.

IMPORTANCE: Although critical to patient safety, health care-related allergic reactions are challenging to identify and monitor.

Improving the taxonomy of fossil pollen using convolutional neural networks and superresolution microscopy.

Taxonomic resolution is a major challenge in palynology, largely limiting the ecological and evolutionary interpretations possible with deep-time foss...

Knowledge gaps in immune response and immunotherapy involving nanomaterials: Databases and artificial intelligence for material design.

Exploring the interactions between the immune system and nanomaterials (NMs) is critical for designing effective and safe NMs, but large knowledge gap...

ProIn-Fuse: improved and robust prediction of proinflammatory peptides by fusing of multiple feature representations.

A proinflammatory peptide (PIP) is a type of signaling molecules that are secreted from immune cells, which contributes to the first line of defense a...

Successful Treatment of Allergic Bronchopulmonary Aspergillosis Using a Combination of Inhaled Fluticasone Furoate/Vilanterol and Oral Voriconazole.

Systemic corticosteroids are considered to be the standard treatment for allergic bronchopulmonary aspergillosis (ABPA). However, there is controversy...

Pollen analysis using multispectral imaging flow cytometry and deep learning.

Pollen identification and quantification are crucial but challenging tasks in addressing a variety of evolutionary and ecological questions (pollinati...

Personalized prediction of daily eczema severity scores using a mechanistic machine learning model.

BACKGROUND: Atopic dermatitis (AD) is a chronic inflammatory skin disease with periods of flares and remission. Designing personalized treatment strat...

Wearable multi-sensing double-chain thermoelectric generator.

Wearable electronics play a crucial role in advancing the rapid development of artificial intelligence, and as an attractive future vision, all-in-one...

A novel method based on infrared spectroscopic inception-resnet networks for the detection of the major fish allergen parvalbumin.

We have developed a novel approach that involves inception-resnet network (IRN) modeling based on infrared spectroscopy (IR) for rapid and specific de...

A rapid white blood cell classification system based on multimode imaging technology.

In order to simplify the complexity of white blood cell classification in existing point-of-care testing (POCT) testing equipment, a white blood cell ...

Biomarkers of the Response to Immune Checkpoint Inhibitors in Metastatic Urothelial Carcinoma.

The mechanisms underlying the resistance to immune checkpoint inhibitors (ICIs) therapy in metastatic urothelial carcinoma (mUC) patients are not clea...

Artificial Intelligence and Mechanistic Modeling for Clinical Decision Making in Oncology.

The amount of "big" data generated in clinical oncology, whether from molecular, imaging, pharmacological, or biological origin, brings novel challeng...

Deep learning for genomics using Janggu.

In recent years, numerous applications have demonstrated the potential of deep learning for an improved understanding of biological processes. However...

Precise automatic classification of 46 different pollen types with convolutional neural networks.

In palynology, the visual classification of pollen grains from different species is a hard task which is usually tackled by human operators using micr...

Immunopeptidomic Data Integration to Artificial Neural Networks Enhances Protein-Drug Immunogenicity Prediction.

Recombinant DNA technology has, in the last decades, contributed to a vast expansion of the use of protein drugs as pharmaceutical agents. However, su...

Objective evaluation of allergic conjunctival disease (with a focus on the application of artificial intelligence technology).

We have summarized the past efforts and results of objective measurement methods for conjunctival hyperemia classification. Severity classification us...