Atopy

Powerful Tests for Multi-Marker Association Analysis Using Ensemble Learning.

Multi-marker approaches have received a lot of attention recently in genome wide association studies and can enhance power to detect new associations under certain conditions. Gene-, gene-set- and pathway-based association tests are increasingly being viewed as useful supplements to the more widely used single marker association analysis which have successfully uncovered numerous disease variants....

Yolk sac tumor of the external auditory canal: a case report and literature review.

We report one case of yolk sac tumor of the ear and review the literature. The patient was a 9-month boy who scratched his right ear repeatedly one month ago. Computed tomography scan showed an irregular elongated mass image measuring 42×16 mm was found in the right external auditory canal. The tumor was located underneath of the epidermis with ulceration. Mild or moderate atypical round or oval t...

Neuro-fuzzy classification of asthma and chronic obstructive pulmonary disease.

BACKGROUND: This paper presents a system for classification of asthma and chronic obstructive pulmonary disease (COPD) based on fuzzy rules and the tr...

Identification of novel Xanthomonas euvesicatoria type III effector proteins by a machine-learning approach.

The Gram-negative bacterium Xanthomonas euvesicatoria (Xcv) is the causal agent of bacterial spot disease in pepper and tomato. Xcv pathogenicity depe...

Prediction of drug-induced eosinophilia adverse effect by using SVM and naïve Bayesian approaches.

Drug-induced eosinophilia is a potentially life-threatening adverse effect; clinical manifestations, eosinophilia-myalgia syndrome, mainly include sev...

Selective determination of dimenhydrinate in presence of six of its related substances and potential impurities using a direct GC/MS method.

A novel simple, direct and selective gas chromatography-mass spectrometry (GC/MS) procedure was developed for the determination of the antihistamine d...

Explainable Transformer Models for Clinical Prediction Tasks on Structured Electronic Health Records

Predictive models over structured electronic health records (EHRs) remain central to machine learning for healthcare, but few have jointly emphasized ...

Genetic decoding reveals druggable biology implicitly learned by a medical-history foundation model

Foundation models trained on electronic healthcare records (EHRs) have gained traction with the aim to transform personalised medicine. However, their...

TEDDY: A Pediatric Foundation Model for Risk Forewarning from ICD-Coded Diagnostic Histories

Pediatric electronic health records capture developmentally structured clinical trajectories, yet their potential for generative healthcare foundation...

Effects of gabapentin on ongoing behaviors displayed by mice with chemotherapy neuropathy

Chemotherapy-induced peripheral neuropathy (CIPN) is a common and painful side effect of paclitaxel (PTX) treatment. The most common measures of painf...

Patient-Level Diagnosis of Acute Myeloid Leukemia via Deep Learning Analysis of Bone Marrow Smear

Bone marrow smear review remains important for acute myeloid leukemia (AML) assessment, but manual single-cell interpretation is labor-intensive and p...

Optimizing 2D Input Representations and Sub-phase Fusion Strategies for Differential Diagnosis of Asthma and COPD Using CNN- and GRU-Based Networks

This study aims to explore the performance of the VAR model in comparison with mel-frequency cepstral coefficient (MFCC) matrices and log-mel spectrog...

Case-level artificial intelligence for multi-photo teledermatology submissions: development and internal validation using patient-submitted dermatology images

Background: Store-and-forward teledermatology commonly relies on several patient-submitted photographs of the same concern, but most dermatology artif...

Large language models and retrieval augmented generation for complex clinical codelists: evaluating performance and assessing failure modes

Objectives: Large language models (LLMs) have shown promise in creating clinical codelists for research purposes, a time-consuming task requiring expe...

Physically-Guided Optical Inversion Enable Non-Contact Side-Channel Attack on Isolated Screens

Noncontact exfiltration of electronic screen content poses a security challenge, with side-channel incursions as the principal vector. We introduce an...

Decoding by Perturbation: Mitigating MLLM Hallucinations via Dynamic Textual Perturbation

Multimodal Large Language Models frequently suffer from inference hallucinations, partially stemming from language priors dominating visual evidence. ...

Grading of Erythema and Visual Attributes in Atopic Dermatitis across Diverse Skin Tones Using a Vision AI Pipeline

Background: Atopic dermatitis (AD) is a prevalent chronic inflammatory skin disease associated with clinical, psychosocial, and economic burden. Accur...

An Image Dataset of Common Skin Diseases of Bangladesh and Benchmarking Performance with Machine Learning Models

Skin diseases are a major public health concern worldwide, and their detection is often challenging without access to dermatological expertise. In cou...

When AI Shows Its Work, Is It Actually Working? Step-Level Evaluation Reveals Frontier Language Models Frequently Bypass Their Own Reasoning

Language models increasingly "show their work" by writing step-by-step reasoning before answering. But are these reasoning steps genuinely used, or de...

Exposomics for childhood asthma

Identification of early interventions to reduce/eliminate asthma - the most common chronic disease among children - could significantly reduce burden ...