Dermatology

NIMETOX-informed Precision Nomothetic Models of Major Depressive Disorder: Group, Phenome, and Individual Signatures

Background: Major depressive disorder (MDD) is a neuro-immune-metabolic-oxidative (NIMETOX) disorder. Nevertheless, the effects of alterations in immune responsiveness, oxidative stress, antioxidant defenses, gut-derived short-chain fatty acids (SCFAs), metabolic hormones and adipokines on metabolomic modules and the MDD phenome have remained elusive. Methods: Serum samples from 125 MDD inpatients...

Development of a prediction model for infant hospitalization and death using clinical features assessed by community health workers during routine postnatal home visits in Dhaka, Bangladesh

Introduction: To improve upon the World Health Organization (WHO) 8 danger signs used to identify young infants (<2 months) requiring referral during community health worker (CHW) home visits, aggregative features (e.g., cumulative visits with fever) rather than visit-specific features (e.g., fever at a single visit), and a machine learning random forest model, may enhance predictive performance. ...

Integrating Quantitative Histology with Clinical Data Improves Prediction of Cervical Intraepithelial Neoplasia Regression

Cervical intraepithelial neoplasia grade 2 (CIN2) lesions show variable outcomes, and accurate prediction of regression remains a major clinical chall...

Does medical specialization of VLMs enhance discriminative power?: A comprehensive investigation through feature distribution analysis

This study investigates the feature representations produced by publicly available open source medical vision-language models (VLMs). While medical VL...

Multimodal system for skin cancer detection

Melanoma detection is vital for early diagnosis and effective treatment. While deep learning models on dermoscopic images have shown promise, they req...

DermaBench: A Clinician-Annotated Benchmark Dataset for Dermatology Visual Question Answering and Reasoning

Vision-language models (VLMs) are increasingly important in medical applications; however, their evaluation in dermatology remains limited by datasets...

A Hierarchical Benchmark of Foundation Models for Dermatology

Foundation models have transformed medical image analysis by providing robust feature representations that reduce the need for large-scale task-specif...

Pigment Network Detection and Classification in Dermoscopic Images Using Directional Imaging Algorithms and Convolutional Neural Networks

Early diagnosis of melanoma, which can save thousands of lives, relies heavily on the analysis of dermoscopic images. One crucial diagnostic criterion...

Pairing-free Group-level Knowledge Distillation for Robust Gastrointestinal Lesion Classification in White-Light Endoscopy

White-Light Imaging (WLI) is the standard for endoscopic cancer screening, but Narrow-Band Imaging (NBI) offers superior diagnostic details. A key cha...

Machine learning based diagnostics of veterinary cancer on ultrasound and optical imaging data.

Study advances current diagnostic efficiency of canine/feline (sub-)cutaneous tumors using machine learning and multimodal imaging data. White light (...

FiDTouch: A 3D Wearable Haptic Display for the Finger Pad

The applications of fingertip haptic devices have spread to various fields from revolutionizing virtual reality and medical training simulations to ...

Bluish Veil Detection and Lesion Classification using Custom Deep Learnable Layers with Explainable Artificial Intelligence (XAI)

Melanoma, one of the deadliest types of skin cancer, accounts for thousands of fatalities globally. The bluish, blue-whitish, or blue-white veil (BW...

DpDNet: An Dual-Prompt-Driven Network for Universal PET-CT Segmentation

PET-CT lesion segmentation is challenging due to noise sensitivity, small and variable lesion morphology, and interference from physiological high-m...

Modeling and Reversing Brain Lesions Using Diffusion Models

Brain lesions are abnormalities or injuries in brain tissue that are often detectable using magnetic resonance imaging (MRI), which reveals structur...

HGNet: High-Order Spatial Awareness Hypergraph and Multi-Scale Context Attention Network for Colorectal Polyp Detection

Colorectal cancer (CRC) is closely linked to the malignant transformation of colorectal polyps, making early detection essential. However, current m...

Protocol for a multicenter randomized controlled trial to assess the usefulness of computer-aided detection systems for colonoscopy in colorectal cancer screening in the Asia-Pacific region (project CAD/NCCH2217).

Ensuring the high quality of colonoscopies in colorectal cancer (CRC) screening is essential to reducing CRC. Recently, computer-aided detection syste...

PLUS: Plug-and-Play Enhanced Liver Lesion Diagnosis Model on Non-Contrast CT Scans

Focal liver lesions (FLL) are common clinical findings during physical examination. Early diagnosis and intervention of liver malignancies are cruci...

Advancing Lung Disease Diagnosis in 3D CT Scans

To enable more accurate diagnosis of lung disease in chest CT scans, we propose a straightforward yet effective model. Firstly, we analyze the chara...

Establishment of an intelligent analysis system for clinical image features of melanonychia based on deep learning image segmentation.

Melanonychia, a condition that can be indicative of malignant melanoma, presents a significant challenge in early diagnosis due to the invasive nature...

Clinical Utility Findings of a Transcriptomic Psoriasis Biologic Test Demonstrate Altered Physician Prescribing Behavior and Improved Patient Outcomes.

INTRODUCTION: This randomized, prospective study (MATCH) was designed to assess the clinical utility of a machine learning-based tool (Mind.Px) that p...