Dermatology

Effect of data-driven motion correction for respiratory movement on lesion detectability in PET-CT: a phantom study.

PURPOSE: While data-driven motion correction (DDMC) techniques have proven to enhance the visibility of lesions affected by motion, their impact on overall detectability remains unclear. This study investigates whether DDMC improves lesion detectability in PET-CT using FDG-18F.

Identification of neural crest and melanoma cancer cell invasion and migration genes using high-throughput screening and deep attention networks.

BACKGROUND: Cell migration and invasion are well-coordinated in development and disease but remain poorly understood. We previously showed that the neural crest (NC) cell migratory wavefront shares a 45-gene panel with other cell invasion phenomena. To rapidly and systematically identify critical genes, we performed a high-throughput siRNA screen and statistical and deep learning analyses to deter...

PediMS: A Pediatric Multiple Sclerosis Lesion Segmentation Dataset.

Multiple Sclerosis (MS) is a chronic autoimmune disease that primarily affects the central nervous system and is predominantly diagnosed in adults, ma...

Enhanced melanoma and non-melanoma skin cancer classification using a hybrid LSTM-CNN model.

Melanoma is the most dangerous type of skin cancer. Although it accounts for only about 1% of all skin cancer cases, it is responsible for the majorit...

USP5-Mediated PD-L1 deubiquitination regulates immunotherapy efficacy in melanoma.

BACKGROUND: The role of post-translational modifications(PTMs) in PD-L1-mediated immune resistance and melanoma progression remains poorly understood.

Enhanced detection of Mpox using federated learning with hybrid ResNet-ViT and adaptive attention mechanisms.

Monkeypox (Mpox), caused by the monkeypox virus, has become a global concern due to its rising cases and resemblance to other rash-causing diseases li...

Improved prediction of MAPKi response duration in melanoma patients using genomic data and machine learning.

Baseline genomic data have not demonstrated significant value for predicting the response duration to MAPK inhibitors (MAPKi) in patients with advance...

Explainable deep learning approaches for high precision early melanoma detection using dermoscopic images.

Detecting skin melanoma in the early stage using dermoscopic images presents a complex challenge due to the inherent variability in images. Utilizing ...

Assessing changes in whole-brain structural connectivity in the unilateral 6-hydroxydopamine rat model of Parkinson's disease using diffusion imaging and tractography.

Parkinson's disease (PD) is a multifactorial, progressive neurodegenerative disease that has a profound impact on those it afflicts. Its hallmark path...

Deep Learning Multi Modal Melanoma Detection: Algorithm Development and Validation.

BACKGROUND: The visual similarity of melanoma and seborrheic keratosis has made it difficult for elderly patients with disabilities to know when to se...

Can Whole-Thyroid-Based CT Radiomics Model Achieve the Performance of Lesion-Based Model in Predicting the Thyroid Nodules Malignancy? - A Comparative Study.

Machine learning is now extensively implemented in medical imaging for preoperative risk stratification and post-therapeutic outcome assessment, enhan...

Radiological and Biological Dictionary of Radiomics Features: Addressing Understandable AI Issues in Personalized Prostate Cancer, Dictionary Version PM1.0.

Artificial intelligence (AI) can advance medical diagnostics, but interpretability limits its clinical use. This work links standardized quantitative ...

Diagnosis of psoriasis and lichen planus in real-time using neural networks based on skin Biomechanical properties obtained from numerical simulation.

Due to their similar clinical presentations, the scarcity of competent dermatologists, and the urgency of diagnosis, the accurate diagnosis of dermato...

Stereotactic radiotherapy or protons for uveal melanoma patients? An artificial intelligence (AI)-based clinical treatment decision-making tool predicting doses to radiotherapy constraints.

PURPOSE: For ocular melanoma, selecting between stereotactic radiotherapy (SRT) and protons requires a lengthy plan comparison process. The purpose of...

Cohesive data analysis for the identification of prognostic hub genes and significant pathways associated with HER2 + and TN breast cancer types.

Breast cancer is the most prevalent and lethal form of cancer being the utmost common medical concern of women. Breast cancer etiology implicates nume...

Intelligent diagnosis model for chest X-ray images diseases based on convolutional neural network.

To address misdiagnosis caused by feature coupling in multi-label medical image classification, this study introduces a chest X-ray pathology reasonin...

CLASEG: advanced multiclassification and segmentation for differential diagnosis of oral lesions using deep learning.

Oral cancer has a high mortality rate primarily due to delayed diagnoses, highlighting the need for early detection of oral lesions. This study presen...

Impact of tertiary lymphoid structure-associated biomarkers on pancreatic cancer via a dual-disease analysis of psoriasis and pancreatic cancer.

Pancreatic cancer (PC), often referred to as the "king of cancers", has demonstrated limited success with immunotherapies, many of which are still und...

Design of Block-Scrambling-Based privacy protection mechanism in healthcare using fusion of transfer learning models with Hippopotamus optimization algorithm.

In the human body, the skin is the main organ. Nearly 30-70% of individuals globally have skin-related health issues, for whom efficient and effective...

Deep learning model for hair artifact removal and Mpox skin lesion analysis and detection.

Accurate identification of Mpox is essential for timely diagnosis and treatment. However, traditional image-based diagnostic methods often struggle wi...