Allergy & Immunology

Automated Eosinophil Quantification Using Deep Learning to Predict Therapy Escalation in Pediatric Ulcerative Colitis.

BACKGROUND: Emerging evidence implicates eosinophils as important modulators of disease activity and therapeutic response in ulcerative colitis. Automated image analysis provides a scalable and reproducible approach to their evaluation, overcoming the limitations of manual quantification. METHODS: We developed a U-Net-based deep learning (DL) model to automate eosinophil detection, using whole-sli...

A machine learning-driven framework integrating cell death and senescence signatures for multi-target drug design and immunotherapy optimization in ovarian cancer.

Ovarian cancer (OC) remains therapeutic challenge due to its complex molecular heterogeneity and therapy-induced adaptive resistance. While non-apoptotic cell death and senescence pathways contribute to tumor evolution and immunosuppression, their integration into predictive models for multi-target drug design and immunotherapy optimization is underexplored. Machine learning was used to identify k...

Ai-enhanced clinical decision support reduces medication errors and adverse drug events in a multicenter teaching hospital network: A prospective randomized controlled trial.

BACKGROUND: Medication errors remain a leading source of preventable harm in hospitalized patients, contributing to adverse drug events (ADEs), prolon...

A macrophage co-expression signature enables robust prognostic prediction in glioblastoma.

BACKGROUND: Glioblastoma (GBM) exhibits profound cellular heterogeneity and a highly immunosuppressive microenvironment in which tumor-associated macr...

3D-printed real-time biosensing system integrating deep learning for label-free in vitro T cell culture analysis.

Recent advances in T cell-based immunotherapies highlight the urgent need for precise and dynamic monitoring across the entire cell culture pipeline. ...

Gene-level gut microbiome signatures as predictive biomarkers for response to immune checkpoint inhibitors across multiple cancer types.

Targeting programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) with immune checkpoint inhibitors (ICIs) has...

Comprehensive analysis of predictive models for disease manifestations and case fatality in systemic lupus erythematosus.

This systematic review evaluated the performance and risk of bias in Systemic Lupus Erythematosus (SLE) disease manifestations and case fatality predi...

Key factors of the deranged antiviral response in elderly patients with COVID-19: a machine-learning analysis.

Age is a well-known risk factor to develop severe viral respiratory infections, including severe COVID-19. This study aimed to identify the biological...

Graves' disease: a new era of pathophysiology-guided therapeutics.

Graves' disease (GD) is an autoimmune entity that had an unchanged treatment paradigm for more than half a century with radioactive iodine, antithyroi...

Machine Learning-Based Prediction of Critical Deterioration in the PICU.

BACKGROUND: Existing PICU early warning systems lack sufficient accuracy and timeliness for effective preparation. Machine learning approaches may imp...

Decoding viral evolution through integrative bioinformatics: From genomes to global health.

Bioinformatics has transformed modern virology by linking genomic variation to epidemiology, protein structure, and public health action. This review ...

Transcriptome and single-cell RNA sequencing data identify and validate candidate biomarkers associated with lysosomal and ferroptosis in osteoarthritis.

BACKGROUND: Osteoarthritis (OA) represents the most common degenerative joint disease, with emerging evidence linking it to lysosomal dysfunction and ...

Nanomaterials reshaping cancer radiotherapy: Radiosensitization mechanisms, delivery and theranostic platforms, multimodal synergy, and clinical translation strategies.

Radiotherapy (RT) remains a cornerstone of cancer management but is fundamentally constrained by normal tissue toxicity, intrinsic and acquired radior...

Crosstalk between immune and programmed cell death and their application in colorectal cancer risk stratification.

Programmed cell death (PCD) and cellular immunity play pivotal roles in colorectal cancer (CRC) progression; understanding their crosstalk and identif...

n-Type Polymer Radio Frequency Rectifiers Operating at 18.5 GHz.

As advancements in artificial intelligence, the Internet of Things (IoT), and telecommunication technologies continue to accelerate, the demand for ch...

Cohort vs case-control design for transformer-based prediction of asthma exacerbations in mild asthma.

Acute asthma exacerbation (AAE) is among the most serious outcomes of asthma, and accurate prediction of its risk remains a key challenge. Existing el...

Mortality Prediction Among People Living With HIV on Antiretroviral Therapy in Public Health Facilities in Gondar City Administration, Northwest Ethiopia: Machine Learning-Based Study.

BACKGROUND: Predicting mortality among people living with HIV enables clinicians to implement timely, targeted, and preventive interventions at the st...

Optimal treatment selection for hepatocellular carcinoma in the era of immunotherapy.

Immunotherapy has revolutionized hepatocellular carcinoma (HCC) management, necessitating personalized strategies in current guidelines. Despite curat...

Clinician-deployable deep hypergraph model integrating clinical and CT radiomics predicts immunotherapy outcomes in NSCLC.

Current image-based deep learning models that predict the benefits of immunotherapy in non-small cell lung cancer (NSCLC) require high-performance har...

Harnessing machine learning models to repurpose drugs targeting HIV-1 integrase, protease, and reverse transcriptase.

The human immunodeficiency virus type 1 (HIV-1) is a type of retrovirus responsible for immunodeficiency syndrome, a sickness that significantly compr...