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Skin

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Simultaneous determination and quantitation of hypolipidemic drugs in fingerprints by UPLC-Q-TRAP/MS.

Journal of chromatography. B, Analytical technologies in the biomedical and life sciences
An ultra-performance liquid chromatography tandem triple quadrupole compound linear ion trap mass spectrometry (UPLC-Q-TRAP/MS) method was developed and validated for the detection of hypolipidemic drugs in fingerprints. 13 hypolipidemic drugs were w...

Machine-learning-driven biomarker discovery for the discrimination between allergic and irritant contact dermatitis.

Proceedings of the National Academy of Sciences of the United States of America
Contact dermatitis tremendously impacts the quality of life of suffering patients. Currently, diagnostic regimes rely on allergy testing, exposure specification, and follow-up visits; however, distinguishing the clinical phenotype of irritant and all...

A new deep learning approach integrated with clinical data for the dermoscopic differentiation of early melanomas from atypical nevi.

Journal of dermatological science
BACKGROUND: Timely recognition of malignant melanoma (MM) is challenging for dermatologists worldwide and represents the main determinant for mortality. Dermoscopic examination is influenced by dermatologists' experience and fails to achieve adequate...

Dermal epidermal junction detection for full-field optical coherence tomography data of human skin by deep learning.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Full-field optical coherence tomography (FF-OCT) has been developed to obtain three-dimensional (3D) OCT data of human skin for early diagnosis of skin cancer. Detection of dermal epidermal junction (DEJ), where melanomas and basal cell carcinomas or...

Using Machine Learning Algorithms to Predict Immunotherapy Response in Patients with Advanced Melanoma.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Several biomarkers of response to immune checkpoint inhibitors (ICI) show potential but are not yet scalable to the clinic. We developed a pipeline that integrates deep learning on histology specimens with clinical data to predict ICI respon...

Artificial neural networks and pathologists recognize basal cell carcinomas based on different histological patterns.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Recent advances in artificial intelligence, particularly in the field of deep learning, have enabled researchers to create compelling algorithms for medical image analysis. Histological slides of basal cell carcinomas (BCCs), the most frequent skin t...

A DNA-Based Intelligent Expert System for Personalised Skin-Health Recommendations.

IEEE journal of biomedical and health informatics
Intensive attention on personalised skin-health solutions is on account of incomparable love of skin and an urgent need for effective treatment. In the meanwhile, people have great expectations on how to utilise genetic knowledge of our body to provi...

PyHIST: A Histological Image Segmentation Tool.

PLoS computational biology
The development of increasingly sophisticated methods to acquire high-resolution images has led to the generation of large collections of biomedical imaging data, including images of tissues and organs. Many of the current machine learning methods th...

Facial erythema detects diabetic neuropathy using the fusion of machine learning, random matrix theory and self organized criticality.

Scientific reports
Rubeosis faciei diabeticorum, caused by microangiopathy and characterized by a chronic facial erythema, is associated with diabetic neuropathy. In clinical practice, facial erythema of patients with diabetes is evaluated based on subjective observati...