Dermatology

[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 melano...

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 i...

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 medicin...

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 analysi...

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 t...

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 visu...

Deep Learning based Skin-layer Segmentation for Characterizing Cutaneous Wounds from Optical Coherence Tomography Images.

Optical coherence tomography (OCT) is a medical imaging modality that allows us to probe deeper sub-...

Deep Learning Networks for Breast Lesion Classification in Ultrasound Images: A Comparative Study.

Accurate lesion classification as benign or malignant in breast ultrasound (BUS) images is a critica...

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 mai...

Using artificial intelligence on dermatology conditions in Uganda: a case for diversity in training data sets for machine learning.

BACKGROUND: In pursuit of applying universal non-biased Artificial Intelligence (AI) in healthcare, ...

Combining Deep Learning and Handcrafted Radiomics for Classification of Suspicious Lesions on Contrast-enhanced Mammograms.

Background Handcrafted radiomics and deep learning (DL) models individually achieve good performance...

Artificial Intelligence Solution for Chest Radiographs in Respiratory Outpatient Clinics: Multicenter Prospective Randomized Clinical Trial.

Artificial intelligence (AI)-assisted diagnosis imparts high accuracy to chest radiography (CXR) in...

From eczema to anxiety: How artificial intelligence  shapes parental perspectives.

Machine learning analysis of breast ultrasound to classify triple negative and HER2+ breast cancer subtypes.

OBJECTIVES: Early diagnosis of triple-negative (TN) and human epidermal growth factor receptor 2 pos...

Updates in Cutaneous Oncology.

Cutaneous oncology is currently a rapidly evolving field. Dermoscopy, total body photography, biomar...

3D Visualization of Microtubules in Epidermal Pavement Cells.

The plant cytoskeleton is instrumental in cellular processes such as cell growth, differentiation, a...

Artificial intelligence: Its role in dermatopathology.

Artificial intelligence (AI), a major frontier in the field of medical research, can potentially lea...

An end-to-end multi-task system of automatic lesion detection and anatomical localization in whole-body bone scintigraphy by deep learning.

SUMMARY: Limited by spatial resolution and visual contrast, bone scintigraphy interpretation is susc...

New Horizons: Artificial Intelligence for Digital Breast Tomosynthesis.

The use of digital breast tomosynthesis (DBT) in breast cancer screening has become widely accepted,...

[Deep learning-based fully automated intelligent and precise diagnosis for melanocytic lesions].

Melanocytic lesions occur on the surface of the skin, in which the malignant type is melanoma with a...

BRACS: A Dataset for BReAst Carcinoma Subtyping in H&E Histology Images.

Breast cancer is the most commonly diagnosed cancer and registers the highest number of deaths for w...