AIMC Topic: Psoriasis

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Automatic evaluation of Nail Psoriasis Severity Index using deep learning algorithm.

The Journal of dermatology
Nail psoriasis is a chronic condition characterized by nail dystrophy affecting the nail matrix and bed. The severity of nail psoriasis is commonly assessed using the Nail Psoriasis Severity Index (NAPSI), which evaluates the characteristics and exte...

Deciphering the Genetic Links between Psychological Stress, Autophagy, and Dermatological Health: Insights from Bioinformatics, Single-Cell Analysis, and Machine Learning in Psoriasis and Anxiety Disorders.

International journal of molecular sciences
The relationship between psychological stress, altered skin immunity, and autophagy-related genes (ATGs) is currently unclear. Psoriasis is a chronic skin inflammation of unclear etiology that is characterized by persistence and recurrence. Immune dy...

Discovery of biomarkers in the psoriasis through machine learning and dynamic immune infiltration in three types of skin lesions.

Frontiers in immunology
INTRODUCTION: Psoriasis is a chronic skin disease characterized by unique scaling plaques. However, during the acute phase, psoriatic lesions exhibit eczematous changes, making them difficult to distinguish from atopic dermatitis, which poses challen...

Efficient diagnosis of psoriasis and lichen planus cutaneous diseases using deep learning approach.

Scientific reports
The tendency of skin diseases to manifest in a unique and yet similar appearance, absence of enough competent dermatologists, and urgency of diagnosis and classification on time and accurately, makes the need of machine aided diagnosis blatant. This ...

Human-multimodal deep learning collaboration in 'precise' diagnosis of lupus erythematosus subtypes and similar skin diseases.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: Lupus erythematosus (LE) is a spectrum of autoimmune diseases. Due to the complexity of cutaneous LE (CLE), clinical skin image-based artificial intelligence is still experiencing difficulties in distinguishing subtypes of LE.

Tree-Based Machine Learning to Identify Predictors of Psoriasis Incidence at the Neighborhood Level: A Populational Study from Quebec, Canada.

American journal of clinical dermatology
BACKGROUND: Psoriasis is a major global health burden affecting ~ 60 million people worldwide. Existing studies on psoriasis focused on individual-level health behaviors (e.g. diet, alcohol consumption, smoking, exercise) and characteristics as drive...

Identification of characteristic genes and herbal compounds for the treatment of psoriasis based on machine learning and molecular dynamics simulation.

Journal of biomolecular structure & dynamics
Psoriasis brings economic and mental burdens to patients, the exact etiology and pathogenesis of psoriasis are still unclear. Compounds of herbal medicine have the potential for psoriasis treatment. This study aims to explore the characteristic genes...

Artificial intelligence in psoriasis: Where we are and where we are going.

Experimental dermatology
Artificial intelligence (AI) is a field of computer science that involves the development of programs designed to replicate human cognitive processes and the analysis of complex data. In dermatology, which is predominantly a visual-based diagnostic f...