AIMC Topic: Skin

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AI-powered skin spectral imaging enables instant sepsis diagnosis and outcome prediction in critically ill patients.

Science advances
With sepsis remaining a leading cause of mortality, early identification of patients with sepsis and those at high risk of death is a challenge of high socioeconomic importance. Given the potential of hyperspectral imaging (HSI) to monitor microcircu...

Machine learning-guided anti-photoaging peptides from Chinese giant salamander skin: Efficient preparation and mechanistic insights.

Food chemistry
Collagen peptides are ubiquitously applied in food systems for their versatile bioactivities but face constraints from labor-intensive enzymatic screening and zoonotic risks from terrestrial sources. This study developed machine learning (ML) models ...

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

Scientific reports
Due to their similar clinical presentations, the scarcity of competent dermatologists, and the urgency of diagnosis, the accurate diagnosis of dermatological conditions such as Psoriasis and Lichen Planus is challenging. This study introduces a novel...

A dual encoder network with multiscale feature fusion and multiple pooling channel spatial attention for skin scar image segmentation.

Scientific reports
Skin scar is a prevalent dermatological concern that impacts both aesthetic appearance and psychological well-being, making precise delineation of scar tissue essential for clinical treatment. To address the challenge of scar image segmentation, this...

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

Scientific reports
Accurate identification of Mpox is essential for timely diagnosis and treatment. However, traditional image-based diagnostic methods often struggle with challenges such as body hair obscuring skin lesions and complicating accurate assessment. To addr...

Microrobots for Antibiotic-Resistant Skin Colony Eradication.

ACS applied materials & interfaces
Self-propelled nano- and micromachines have immense potential as autonomous seek-and-act devices in biomedical applications. In this study, we present microrobots constructed with inherently biocompatible materials and propulsion systems tailored to ...

New artificial neural network models for risk assessment of skin sensitization using amino acid derivative assay, KeratinoSens™, human cell line activation test and in silico structural alert parameter.

Regulatory toxicology and pharmacology : RTP
In the next-generation risk assessment (NGRA) of skin sensitization, estimating the point of departure (PoD) is crucial. The murine local lymph node assay (LLNA) has been considered the 'gold standard' for evaluating the skin sensitizing potential of...

Multimodal information structuring with single-layer soft skins and high-density electrical impedance tomography.

Science robotics
The human skin can reliably capture a wide range of multimodal data over a large surface while providing a soft interface. Artificial technologies using microelectromechanical systems (MEMS) can emulate these biological functions but present numerous...

Lesion boundary detection for skin lesion segmentation based on boundary sensing and CNN-transformer fusion networks.

Artificial intelligence in medicine
Traditional convolutional neural networks often struggle to capture global information and handle ambiguous boundaries during complex skin lesion segmentation tasks. To tackle this challenge, we proposed MPBA-Net, a hybrid network that integrates mul...

Machine learning-based text mining for cutaneous myiasis and potential value of an accidental maggot therapy for complicated skin and soft tissue infection with sepsis.

Frontiers in cellular and infection microbiology
BACKGROUND: Cutaneous myiasis, one of the most frequently diagnosed myiasis types, is defined as skin or soft tissue on a living host infested by dipterous larvae (maggots). However, bibliometric analysis of this disease remains sparse. Machine learn...