Allergy

Machine learning based on blood test biomarkers predicts fast progression in advanced NSCLC patients treated with immunotherapy.

OBJECTIVE: Fast progression (FP) represents a desperate situation for advanced non-small cell lung cancer (NSCLC) patients undergoing immune checkpoint inhibitor therapy. We aimed to develop a predictive framework based on machine learning (ML) methods to identify FP in advanced NSCLC patients using blood test biomarkers.

An Overview of Advances in Rare Cancer Diagnosis and Treatment.

Cancer stands as the leading global cause of mortality, with rare cancer comprising 230 distinct subtypes characterized by infrequent incidence. Despite the inherent challenges in addressing the diagnosis and treatment of rare cancers due to their low occurrence rates, several biomedical breakthroughs have led to significant advancement in both areas. This review provides a comprehensive overview ...

Predicting Penicillin Allergy: A United States Multicenter Retrospective Study.

BACKGROUND: Using the reaction history in logistic regression and machine learning (ML) models to predict penicillin allergy has been reported based o...

A breast cancer-specific combinational QSAR model development using machine learning and deep learning approaches.

Breast cancer is the most prevalent and heterogeneous form of cancer affecting women worldwide. Various therapeutic strategies are in practice based o...

Perioperative Fluid and Vasopressor Therapy in 2050: From Experimental Medicine to Personalization Through Automation.

Intravenous (IV) fluids and vasopressor agents are key components of hemodynamic management. Since their introduction, their use in the perioperative ...

Reliability of large language models in managing odontogenic sinusitis clinical scenarios: a preliminary multidisciplinary evaluation.

PURPOSE: This study aimed to evaluate the utility of large language model (LLM) artificial intelligence tools, Chat Generative Pre-Trained Transformer...

Historical perspective and future directions: computational science in immuno-oncology.

Immuno-oncology holds promise for transforming patient care having achieved durable clinical response rates across a variety of advanced and metastati...

Association between household income levels and nutritional intake of allergic children under 6 years of age in Korea: 2019 Korea National Health and Nutrition Examination Survey and application of machine learning.

INTRODUCTION: This study investigated the prevalence of allergic diseases in Korean children aged 6 and below, focusing on the interplay between nutri...

Refining mutanome-based individualised immunotherapy of melanoma using artificial intelligence.

Using the particular nature of melanoma mutanomes to develop medicines that activate the immune system against specific mutations is a game changer in...

A large language model artificial intelligence for patient queries in atopic dermatitis.

iTTCA-MVL: A multi-view learning model based on physicochemical information and sequence statistical information for tumor T cell antigens identification.

Immunotherapy is an emerging treatment method aimed at activating the human immune system and relying on its own immune function to kill cancer cells ...

Addressing diagnostic dilemmas in eosinophilic esophagitis using esophageal epithelial eosinophil-derived neurotoxin.

OBJECTIVES: Eosinophil-derived neurotoxin (EDN) is a viable marker of eosinophilic esophagitis (EoE) disease activity. We studied the utility of measu...

Screening biomarkers for spinal cord injury using weighted gene co-expression network analysis and machine learning.

JOURNAL/nrgr/04.03/01300535-202412000-00028/figure1/v/2024-04-08T165401Z/r/image-tiff Immune changes and inflammatory responses have been identified a...

Transfer learning improves pMHC kinetic stability and immunogenicity predictions.

The cellular immune response comprises several processes, with the most notable ones being the binding of the peptide to the Major Histocompability Co...

Microsatellite Instability, Mismatch Repair, and Tumor Mutation Burden in Lung Cancer.

Since US Food and Drug Administration approval of programmed death ligand 1 (PD-L1) as the first companion diagnostic for immune checkpoint inhibitors...

Evaluation of atopic dermatitis severity using artificial intelligence.

Atopic dermatitis is a prevalent and persistent chronic inflammatory skin disorder that poses significant challenges when it comes to accurately asses...

Artificial intelligence applications in allergic rhinitis diagnosis: Focus on ensemble learning.

BACKGROUND: The diagnosis of allergic rhinitis (AR) primarily relies on symptoms and laboratory examinations. Due to limitations in outpatient setting...

The tumor immune microenvironment in pancreatic cancer and its potential in the identification of immunotherapy biomarkers.

INTRODUCTION: Pancreatic cancer (PC) has an extremely poor prognosis, even with surgical resection and triplet chemotherapy treatment. Cancer immunoth...

A 13.2 mg epinephrine intranasal spray demonstrates comparable pharmacokinetics, pharmacodynamics, and safety to a 0.3 mg epinephrine autoinjector.

BACKGROUND: Recent acute anaphylaxis guideline updates have identified remaining unmet needs based on currently available therapeutic options as a cri...

Food protein-induced allergic proctocolitis in infants is associated with low serum levels of macrophage inflammatory protein-3a.

BACKGROUND: Food protein-induced allergic proctocolitis (FPIAP) is a nonimmunoglobulin (IgE)-mediated food hypersensitivity and the exact mechanisms t...