AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Psoriasis

Showing 1 to 10 of 60 articles

Clear Filters

Real-World Screening Data for Liver Fibrosis in Psoriasis Patients Treated with Biologics.

Journal of Nippon Medical School = Nippon Ika Daigaku zasshi
BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) is positively associated with the prevalence and severity of psoriasis. The fibrosis-4 (FIB-4) index was developed to predict significant liver fibrosis. Using the FIB-4 ind...

Psoriatic arthritis in psoriasis: optimizing the current screening system for psoriatic arthritis based on serum data from U.S. and Chinese populations.

Frontiers in immunology
BACKGROUND: Psoriatic arthritis (PSA) is an inflammatory joint disease associated with psoriasis (PSO) that can be easily missed. Existing PSA screening tools ignore objective serologic indicators. The aim of this study was to develop a disease scree...

Psoriasis severity assessment: Optimizing diagnostic models with deep learning.

Narra J
Psoriasis is a chronic skin condition with challenges in the accurate assessment of its severity due to subtle differences between severity levels. The aim of this study was to evaluate deep learning models for automated classification of psoriasis s...

Unveiling the molecular mechanisms of Haitang-Xiaoyin Mixture in psoriasis treatment based on bioinformatics, network pharmacology, machine learning, and molecular docking verification.

Computational biology and chemistry
OBJECTIVE: Psoriasis is a common clinical skin inflammatory disease. Haitang-Xiaoyin Mixture (HXM) represents a traditional Chinese medicine formulation utilized clinically for the management of psoriasis, which can reduce the psoriasis area and seve...

A new era of psoriasis treatment: Drug repurposing through the lens of nanotechnology and machine learning.

International journal of pharmaceutics
Psoriasis is a persistent inflammatory skin disorder characterized by hyper-proliferation and abnormal epidermal differentiation. Conventional treatments such as; topical therapies, phototherapy, systemic immune modulators, and biologics aim to relie...

Personalized prediction of psoriasis relapse post-biologic discontinuation: a machine learning-driven population cohort study.

The Journal of dermatological treatment
BACKGROUND: Identifying the risk of psoriasis relapse after discontinuing biologics can help optimize treatment strategies, potentially reducing relapse rates and alleviating the burden of disease management.

Modifying the severity and appearance of psoriasis using deep learning to simulate anticipated improvements during treatment.

Scientific reports
A neural network was trained to generate synthetic images of severe and moderate psoriatic plaques, after being trained on 375 photographs of patients with psoriasis taken in a clinical setting. A latent w-space vector was identified that allowed the...

An interpretable machine learning approach for detecting psoriatic arthritis in a UK primary care psoriasis cohort using electronic health records from the Clinical Practice Research Datalink.

Annals of the rheumatic diseases
OBJECTIVES: Develop an interpretable machine learning model to detect patients with newly diagnosed psoriatic arthritis (PsA) in a cohort of psoriasis patients and identify important clinical indicators of PsA in primary care.

Identification of novel IL17-related genes as prognostic and therapeutic biomarkers of psoriasis using comprehensive bioinformatics analysis and machine learning.

Scientific reports
Psoriasis is a common chronic skin disorder with a polygenic background. It is widely acknowledged that Th17/IL-17A axis plays a key role in the pathogenesis of psoriasis. However, numerous regulatory genes upstream of the pathway remain undiscovered...