Dermatology

MSPA-DLA++: A Multi-Scale Phase Attention Deep Layer Aggregation for Lesion Detection in Multi-Phase CT Images.

Object detection using convolutional neural networks (CNNs) has achieved high performance and achieved state-of-the-art results with natural images. Compared to natural images, medical images present several challenges for lesion detection. First, the sizes of lesions vary tremendously, from several millimeters to several centimeters. Scale variations significantly affect lesion detection accuracy...

Stratum corneum nanotexture feature detection using deep learning and spatial analysis: a noninvasive tool for skin barrier assessment.

BACKGROUND: Corneocyte surface nanoscale topography (nanotexture) has recently emerged as a potential biomarker for inflammatory skin diseases, such as atopic dermatitis (AD). This assessment method involves quantifying circular nano-size objects (CNOs) in corneocyte nanotexture images, enabling noninvasive analysis via stratum corneum (SC) tape stripping. Current approaches for identifying CNOs r...

Robust Visual Identification of Under-resourced Dermatological Diagnoses with Classifier-Steered Background Masking.

Collecting images of rare dermatological diseases for machine learning detection applications is a costly, laborious task. It is difficult to collect ...

Automated cutaneous squamous cell carcinoma grading using deep learning with transfer learning.

INTRODUCTION: Histological grading of cutaneous squamous cell carcinoma (cSCC) is crucial for prognosis and treatment decisions, but manual grading is...

Radiomics and Artificial Intelligence in Renal Lesion Assessment.

Radiomics, the extraction and analysis of quantitative features from medical images, has emerged as a promising field in radiology with the potential ...

Deep learning approach for skin melanoma and benign classification using empirical wavelet decomposition.

BACKGROUND: Melanoma is a malignant skin cancer that causes high mortality. Early detection of melanoma can save patients' lives. The features of the ...

Artificial intelligence's contribution to early pulmonary lesion detection in chest X-rays: insights from two retrospective studies on a Czech population.

In recent years healthcare is undergoing significant changes due to technological innovations, with Artificial Intelligence (AI) being a key trend. Pa...

SkinLiTE: Lightweight Supervised Contrastive Learning Model for Enhanced Skin Lesion Detection and Disease Typification in Dermoscopic Images.

INTRODUCTION: This study introduces SkinLiTE, a lightweight supervised contrastive learning model tailored to enhance the detection and typification o...

Modelling a self-defined CNN for effectual classification of PCOS from ultrasound images.

BACKGROUND: Polycystic Ovary Syndrome (PCOS) is a medical condition that causes hormonal disorders in women in their childbearing years. The hormonal ...

Real-World Screening Data for Liver Fibrosis in Psoriasis Patients Treated with Biologics.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) is positively associated with the prevalence and severity of psoriasis. T...

[MOCK MOLE: PRODUCING SYNTHETIC IMAGES THAT RECAPITULATE CONFOCAL PATTERNS OF MELANOCYTIC NEVI VIA DEEP-LEARNING MODELS].

INTRODUCTION: Melanocytic nevi present microscopic patterns, which differ in their associated melanoma risk, and can be non-invasively recognized unde...

[Axillary Lymph Node Recurrence after Curative Surgery for Transverse Colon Cancer-A Case Report].

We report the rare case of an 89-year-old female with axillary lymph node recurrence after curative surgery for transverse colon cancer who had underg...

IgE anti-BP180 NC16A autoantibody in both serum and blister fluid samples does not correlate with disease activity of bullous pemphigoid.

The correlation between IgE anti-BP180 NC16A autoantibody and disease activity of bullous pemphigoid (BP) remains disputable. To determine the levels ...

Skin Changes in Suspected Lyme Disease.

Dear Editor, Ticks carry many diseases, bacteria, and viruses and represent a very important healthcare issue both in Croatia and globally. Although m...

THItoGene: a deep learning method for predicting spatial transcriptomics from histological images.

Spatial transcriptomics unveils the complex dynamics of cell regulation and transcriptomes, but it is typically cost-prohibitive. Predicting spatial g...

Past, present, and future of global research on artificial intelligence applications in dermatology: A bibliometric analysis.

In recent decades, artificial intelligence (AI) has played an increasingly important role in medicine, including dermatology. Worldwide, numerous stud...

Segmentation and classification of skin lesions using hybrid deep learning method in the Internet of Medical Things.

INTRODUCTION: Particularly within the Internet of Medical Things (IoMT) context, skin lesion analysis is critical for precise diagnosis. To improve th...

Automated detection of apoptotic bodies and cells in label-free time-lapse high-throughput video microscopy using deep convolutional neural networks.

MOTIVATION: Reliable label-free methods are needed for detecting and profiling apoptotic events in time-lapse cell-cell interaction assays. Prior stud...

Unveiling the power of convolutional neural networks in melanoma diagnosis.

Convolutional neural networks are a type of deep learning algorithm. They are mostly applied in visual recognition and can be used for the identificat...

Comparative analysis of deep learning methods for lesion detection on full screening mammography.

Breast cancer is the most prevalent type of cancer in women. Although mammography is used as the main imaging modality for the diagnosis, robust lesio...