AI Medical Compendium Topic

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Skin

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Training artificial neural networks using self-organizing migrating algorithm for skin segmentation.

Scientific reports
This study presents an application of the self-organizing migrating algorithm (SOMA) to train artificial neural networks for skin segmentation tasks. We compare the performance of SOMA with popular gradient-based optimization methods such as ADAM and...

Deep Learning-Based Classification of Early-Stage Mycosis Fungoides and Benign Inflammatory Dermatoses on H&E-Stained Whole-Slide Images: A Retrospective, Proof-of-Concept Study.

The Journal of investigative dermatology
The diagnosis of early-stage mycosis fungoides (MF) is challenging owing to shared clinical and histopathological features with benign inflammatory dermatoses. Recent evidence has shown that deep learning (DL) can assist pathologists in cancer classi...

Squid-Inspired Anti-Salt Skin-Like Elastomers With Superhigh Damage Resistance for Aquatic Soft Robots.

Advanced materials (Deerfield Beach, Fla.)
Cephalopod skins evolve multiple functions in response to environmental adaptation, encompassing nonlinear mechanoreponse, damage tolerance property, and resistance to seawater. Despite tremendous progress in skin-mimicking materials, the integration...

Image-Based Artificial Intelligence in Psoriasis Assessment: The Beginning of a New Diagnostic Era?

American journal of clinical dermatology
Psoriasis, a chronic inflammatory skin disease, affects millions of people worldwide. It imposes a significant burden on patients' quality of life and healthcare systems, creating an urgent need for optimized diagnosis, treatment, and management. In ...

Multi-receptor skin with highly sensitive tele-perception somatosensory.

Science advances
The limitations and complexity of traditional noncontact sensors in terms of sensitivity and threshold settings pose great challenges to extend the traditional five human senses. Here, we propose tele-perception to enhance human perception and cognit...

Radiomic and deep learning analysis of dermoscopic images for skin lesion pattern decoding.

Scientific reports
This study aims to explore the efficacy of a hybrid deep learning and radiomics approach, supplemented with patient metadata, in the noninvasive dermoscopic imaging-based diagnosis of skin lesions. We analyzed dermoscopic images from the Internationa...

MASDF-Net: A Multi-Attention Codec Network with Selective and Dynamic Fusion for Skin Lesion Segmentation.

Sensors (Basel, Switzerland)
Automated segmentation algorithms for dermoscopic images serve as effective tools that assist dermatologists in clinical diagnosis. While existing deep learning-based skin lesion segmentation algorithms have achieved certain success, challenges remai...

Semantic segmentation in skin surface microscopic images with artifacts removal.

Computers in biology and medicine
Skin surface imaging has been used to examine skin lesions with a microscope for over a century and is commonly known as epiluminescence microscopy, dermatoscopy, or dermoscopy. Skin surface microscopy has been recommended to reduce the necessity of ...

AcousTac: Tactile Sensing with Acoustic Resonance for Electronics-Free Soft Skin.

Soft robotics
Sound is a rich information medium that transmits through air; people communicate through speech and can even discern material through tapping and listening. To capture frequencies in the human hearing range, commercial microphones typically have a s...

Intelligent skin-removal photoacoustic computed tomography for human based on deep learning.

Journal of biophotonics
Photoacoustic computed tomography (PACT) has centimeter-level imaging ability and can be used to detect the human body. However, strong photoacoustic signals from skin cover deep tissue information, hindering the frontal display and analysis of photo...