Dermatology

Non-parametric Bayesian deep learning approach for whole-body low-dose PET reconstruction and uncertainty assessment.

Positron emission tomography (PET) imaging plays a pivotal role in oncology for the early detection of metastatic tumors and response to therapy assessment due to its high sensitivity compared to anatomical imaging modalities. The balance between image quality and radiation exposure is critical, as reducing the administered dose results in a lower signal-to-noise ratio (SNR) and information loss, ...

KanCell: dissecting cellular heterogeneity in biological tissues through integrated single-cell and spatial transcriptomics.

KanCell is a deep learning model based on Kolmogorov-Arnold networks (KAN) designed to enhance cellular heterogeneity analysis by integrating single-cell RNA sequencing and spatial transcriptomics (ST) data. ST technologies provide insights into gene expression within tissue context, revealing cellular interactions and microenvironments. To fully leverage this potential, effective computational mo...

The role of CTGF and MFG-E8 in the prognosis assessment of SCAP: a study combining machine learning and nomogram analysis.

BACKGROUND: Severe Community-Acquired Pneumonia (SCAP) is a serious global health issue with high incidence and mortality rates. In recent years, the ...

Multimodal integration using a machine learning approach facilitates risk stratification in HR+/HER2- breast cancer.

Hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) breast cancer is the most common type of breast cancer, with...

Minimal sourced and lightweight federated transfer learning models for skin cancer detection.

One of the most fatal diseases that affect people is skin cancer. Because nevus and melanoma lesions are so similar and there is a high likelihood of ...

Advanced Deep Learning Models for Melanoma Diagnosis in Computer-Aided Skin Cancer Detection.

The most deadly type of skin cancer is melanoma. A visual examination does not provide an accurate diagnosis of melanoma during its early to middle st...

Unlocking Responsive and Unresponsive Signatures: A Transfer Learning Approach for Automated Classification in Cutaneous Leishmaniasis Lesions.

Cutaneous leishmaniasis (CL) remains a significant global public health disease, with the critical distinction and exact detection between responsive ...

A Machine Learning Model for Predicting the HER2 Positive Expression of Breast Cancer Based on Clinicopathological and Imaging Features.

RATIONALE AND OBJECTIVES: To develop a machine learning (ML) model based on clinicopathological and imaging features to predict the Human Epidermal Gr...

Enhancing lesion detection in automated breast ultrasound using unsupervised multi-view contrastive learning with 3D DETR.

The inherent variability of lesions poses challenges in leveraging AI in 3D automated breast ultrasound (ABUS) for lesion detection. Traditional metho...

Artificial Neural Network-Based Validation, DFT, Thermal and Biological Evaluation of 4-Aminoantipyrine-Derived Ru(III) Complexes.

New methodologies have been evaluated for validating analytical characterization with artificial neural networks (ANNs). Compared to previous machine ...

Exploring the anticancer activities of Sulfur and magnesium oxide through integration of deep learning and fuzzy rough set analyses based on the features of Vidarabine alkaloid.

Drug discovery and development is a challenging and time-consuming process. Laboratory experiments conducted on Vidarabine showed IC 6.97 µg∕mL, 25.78...

Artificial Intelligence-Powered Human Epidermal Growth Factor Receptor 2 and Tumor Microenvironment Analysis in Human Epidermal Growth Factor Receptor 2-Amplified Metastatic Colorectal Cancer: Exploratory Analysis of Phase II TRIUMPH Trial.

PURPOSE: Human epidermal growth factor receptor 2 (HER2)-targeted therapies have shown promise in treating -amplified metastatic colorectal cancer (mC...

Deep learning-based skin lesion analysis using hybrid ResUNet++ and modified AlexNet-Random Forest for enhanced segmentation and classification.

Skin cancer is considered globally as the most fatal disease. Most likely all the patients who received wrong diagnosis and low-quality treatment die ...

Frontal fibrosing alopecia part I - Diagnosis and clinical presentation.

Frontal fibrosing alopecia (FFA) is a primary lymphocytic cicatricial alopecia predominantly affecting postmenopausal Caucasian women. It is character...

Unveiling the molecular mechanisms of Haitang-Xiaoyin Mixture in psoriasis treatment based on bioinformatics, network pharmacology, machine learning, and molecular docking verification.

OBJECTIVE: Psoriasis is a common clinical skin inflammatory disease. Haitang-Xiaoyin Mixture (HXM) represents a traditional Chinese medicine formulati...

Generative Adversarial Networks With Radiomics Supervision for Lung Lesion Generation.

Data-driven methods for lesion generation are quickly emerging due to the need for realistic imaging targets for image quality assessment and virtual ...

Effects of UV-B light exposure during automatic milking on vitamin D levels in Holstein Friesian cows.

Vitamin D is essential for cattle and can be synthesized in the skin under ultraviolet irradiation. This study investigated the effects of narrow-band...

Identifying effective immune biomarkers in alopecia areata diagnosis based on machine learning methods.

BACKGROUND: Alopecia areata (AA) is a common non-scarring hair loss disorder associated with autoimmune conditions. However, the pathobiology of AA is...

Elevated serum CA 19-9 level mimicking pancreaticobiliary carcinoma from a hepatic abscess: case report and literature review.

Serum levels of the tumor marker CA 19-9 are widely utilized in the diagnosis and monitoring pancreatic and biliary malignancies. However, serum level...

Diagnosis and prognosis of melanoma from dermoscopy images using machine learning and deep learning: a systematic literature review.

BACKGROUND: Melanoma is a highly aggressive skin cancer, where early and accurate diagnosis is crucial to improve patient outcomes. Dermoscopy, a non-...