AIMC Topic: Psoriasis
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Deep learning approach to skin layers segmentation in inflammatory dermatoses.
Ultrasonics
Mar 21, 2021
Monitoring skin layers with medical imaging is critical to diagnosing and treating patients with chronic inflammatory skin diseases. The high-frequency ultrasound (HFUS) makes it possible to monitor skin condition in different dermatoses. Accurate an...
Accurate surface ultraviolet radiation forecasting for clinical applications with deep neural network.
Scientific reports
Mar 3, 2021
Exposure to appropriate doses of UV radiation provides enormously health and medical treatment benefits including psoriasis. Typical hospital-based phototherapy cabinets contain a bunch of artificial lamps, either broad-band (main emission spectrum 2...
A deep learning system for differential diagnosis of skin diseases.
Nature medicine
May 18, 2020
Skin conditions affect 1.9 billion people. Because of a shortage of dermatologists, most cases are seen instead by general practitioners with lower diagnostic accuracy. We present a deep learning system (DLS) to provide a differential diagnosis of sk...
Melanoma
Skin Neoplasms
Carcinoma, Basal Cell
Carcinoma, Squamous Cell
Humans
Female
Indians, North American
Psoriasis
Diagnosis, Differential
Dermatologists
Skin Diseases
Adult
Male
Middle Aged
Deep Learning
Acne Vulgaris
Asian
Photography
Nurse Practitioners
Alaska Natives
Dermatitis, Seborrheic
Native Hawaiian or Pacific Islander
Folliculitis
Hispanic or Latino
Black or African American
Keratosis, Seborrheic
Telemedicine
Eczema
Warts
White People
Physicians, Primary Care
Observer-independent assessment of psoriasis-affected area using machine learning.
Journal of the European Academy of Dermatology and Venereology : JEADV
Jan 23, 2020
BACKGROUND: Assessment of psoriasis severity is strongly observer-dependent, and objective assessment tools are largely missing. The increasing number of patients receiving highly expensive therapies that are reimbursed only for moderate-to-severe ps...
Application of machine learning to determine top predictors of noncalcified coronary burden in psoriasis: An observational cohort study.
Journal of the American Academy of Dermatology
Oct 31, 2019
BACKGROUND: Psoriasis is associated with elevated risk of heart attack and increased accumulation of subclinical noncalcified coronary burden by coronary computed tomography angiography (CCTA). Machine learning algorithms have been shown to effective...
Smart identification of psoriasis by images using convolutional neural networks: a case study in China.
Journal of the European Academy of Dermatology and Venereology : JEADV
Oct 17, 2019
BACKGROUND: Psoriasis is a chronic inflammatory skin disease, which holds a high incidence in China. However, professional dermatologists who can diagnose psoriasis early and correctly are insufficient in China, especially in the rural areas. A smart...
Natural language processing of Reddit data to evaluate dermatology patient experiences and therapeutics.
Journal of the American Academy of Dermatology
Jul 12, 2019
BACKGROUND: There is a lack of research studying patient-generated data on Reddit, one of the world's most popular forums with active users interested in dermatology. Techniques within natural language processing, a field of artificial intelligence, ...
Serum Procalcitonin and Presepsin Levels in Patients with Generalized Pustular Psoriasis.
Disease markers
Dec 16, 2018
Patients with generalized pustular psoriasis (GPP) often present with symptoms that must be differentiated from sepsis. Procalcitonin (PCT) and presepsin (P-SEP) are widely used as biomarkers for sepsis; therefore, we examined the serum PCT and P-SEP...
Psoriasis skin biopsy image segmentation using Deep Convolutional Neural Network.
Computer methods and programs in biomedicine
Feb 6, 2018
BACKGROUND AND OBJECTIVE: Development of machine assisted tools for automatic analysis of psoriasis skin biopsy image plays an important role in clinical assistance. Development of automatic approach for accurate segmentation of psoriasis skin biopsy...
Random Bits Forest: a Strong Classifier/Regressor for Big Data.
Scientific reports
Jul 22, 2016
Efficiency, memory consumption, and robustness are common problems with many popular methods for data analysis. As a solution, we present Random Bits Forest (RBF), a classification and regression algorithm that integrates neural networks (for depth),...
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