Dermatology

BigEye: a clinically interpretable deep learning framework for diabetic retinopathy detection and stage prediction.

Diabetic Retinopathy (DR) is a major cause of vision loss and blindness in diabetic individuals. DR is conventionally diagnosed by assessing retinal lesion findings from fundus photographs taken during exams and applying a scale like International Classification of Diabetic Retinopathy (ICDR). The expected rise in future DR cases highlights the need for deep learning models capable of identifying ...

Increased Prevalence of Extrathymic Neoplasms in Myasthenia Gravis Patients-A Population-Based, Matched Case-Control Study.

INTRODUCTION/AIMS: Myasthenia gravis (MG) is associated with thymic neoplasms. However, an increased prevalence of extrathymic neoplasms has also been reported. This study aimed to evaluate the rates of malignancy in MG patients while accounting for risk factors such as disease characteristics and immunomodulatory treatments. METHODS: We conducted a case-control study using the Clalit Health Servi...

Semi-Automatic Assessment of Crohn's Disease Activity by Combined Analysis of Bowel Lesions and Creeping Fat.

PURPOSE: To develop and evaluate Crohn-BOOST, an open-source tool enabling semi-automatic segmentation of intestinal lesions and creeping fat on magne...

A multi-modal deep learning network for the classification of paramagnetic rim and remyelinated lesions in multiple sclerosis.

OBJECTIVES: Robust automated classification of paramagnetic rim lesions (PRLs) and remyelinated lesions based on iron and myelin content in people wit...

Classification of suicide attempt history in adolescents with affective disorders: An exploratory machine learning study.

INTRODUCTION: Diagnosis of affective disorders among adolescent population links with the high risk of suicide attempt. The use of clinical psychologi...

Advances in the application of photodynamic diagnosis in Skin Tumors.

Photodynamic Diagnosis (PDD) is a non-invasive imaging technique. It relies on a photosensitizer that, when activated by a specific light source, caus...

Image segmentation of cervical grainy sandy patches lesions associated with female genital schistosomiasis using deep convolutional neural network with U-NET architecture.

Female genital schistosomiasis (FGS) is a neglected but highly prevalent disease in sub-Saharan Africa, caused by Schistosoma haematobium egg-induced ...

Automated detection of new cerebral infarctions and prognostic implications using deep learning on serial MRI.

We developed and externally validated a deep learning model to automatically detect new ischemic lesions on serial FLAIR MRI scans in patients with st...

Identifying Shared Diagnostic Genes and Underlying Mechanisms Between Skin Exposure to Air Pollution and Skin Barrier Damage: A Bioinformatics Approach.

Air pollution poses a significant threat to skin health, contributing to inflammation, aging, and disruption of the epidermal barrier. This study aims...

Bioinspired Keratin-Based Eutectic Hydrogels for Intelligent Health Monitoring and Photothermal Therapy.

The development of epidermal sensors that integrate high mechanical strength, excellent sensing performance, self-healing capability, and monitoring a...

Predicting the Severity of Infrapopliteal Artery Lesions in Patients With Peripheral Artery Disease Using Interpretable Machine Learning.

PURPOSE: Infrapopliteal arterial disease represents a complex subtype of peripheral artery disease (PAD). This study aimed to develop an interpretable...

Reflectance confocal microscopy in the management of lentigo maligna and lentigo maligna melanoma: a systematic review.

BACKGROUND: Lentigo maligna (LM) and lentigo maligna melanoma (LMM) are difficult to manage because of their subclinical extension and ill-defined mar...

Deep Learning-Based Vitiligo Activity Evaluation Using Wood's Lamp Imaging: A Clinical Decision Support.

Vitiligo is an autoimmune disorder characterized by heterogeneous and unpredictable depigmentation, which poses substantial challenges for objective d...

CTP-Free Method for Automated Lesion Water Uptake in Acute Ischemic Stroke.

BACKGROUND AND PURPOSE: Net water uptake (NWU) in the infarct core of patients with ischemic stroke has been correlated with clinical outcome and lesi...

Machine Learning-Based Preoperative Predicting TERT Promoter Mutation and EGFR Gene Amplification Phenotype in IDH Wild-Type Glioblastoma Using Advanced MR Habitat Imaging.

BACKGROUND AND PURPOSE: The telomerase reverse transcriptase (TERT) gene promoter mutation is a crucial factor for identifying an isocitrate dehydroge...

Proteomics-based machine learning model for predicting secondary infection in HBV-related liver failure.

Patients with Hepatitis B Virus-related liver failure are highly vulnerable to secondary infections (SI), yet early predictive tools remain limited. I...

An IoT-enabled CRNN framework for secure wearable sensor-based activity recognition in physical education.

Recent advancements in digital technologies have profoundly transformed healthcare delivery, sports analytics, and physical activity surveillance. The...

Hoof lesion detection in lactating Holsteins: Part II. Development and on-farm validation of a predictive classification model using autonomous camera system data compared to passive surveillance.

Hoof lesion detection remains a challenge in lameness management on dairy farms. Recent studies have proposed locomotion score (LS)-based thresholds u...

AutoPET Challenge on Fully Automated Lesion Segmentation in Oncologic PET/CT Imaging, Part 2: Domain Generalization.

This article reports the results of the second iteration of the autoPET challenge on automated lesion segmentation in whole-body PET/CT, held in conju...

Forensic 3D avatars - AI-assisted injury detection and interactive digital-twin visualization.

This feasibility study explores the application of a dermatology-based 3D full-body scanning system (VECTRA WB360) combined with artificial intelligen...