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Psoriasis

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Assessing the response quality and readability of chatbots in cardiovascular health, oncology, and psoriasis: A comparative study.

International journal of medical informatics
BACKGROUND: Chatbots using the Large Language Model (LLM) generate human responses to questions from all categories. Due to staff shortages in healthcare systems, patients waiting for an appointment increasingly use chatbots to get information about ...

The circadian syndrome is a better predictor for psoriasis than the metabolic syndrome via an explainable machine learning method - the NHANES survey during 2005-2006 and 2009-2014.

Frontiers in endocrinology
OBJECTIVE: To explore the association between circadian syndrome (CircS) and Metabolic Syndrome (MetS) with psoriasis. Compare the performance of MetS and CircS in predicting psoriasis.

The state of artificial intelligence for systemic dermatoses: Background and applications for psoriasis, systemic sclerosis, and much more.

Clinics in dermatology
Artificial intelligence (AI) has been steadily integrated into dermatology, with AI platforms already attempting to identify skin cancers and diagnose benign versus malignant lesions. Although not as widely known, AI programs have also been utilized ...

Deep learning-assisted multispectral imaging for early screening of skin diseases.

Photodiagnosis and photodynamic therapy
INTRODUCTION: Melanocytic nevi (MN), warts, seborrheic keratoses (SK), and psoriasis are four common types of skin surface lesions that typically require dermatoscopic examination for definitive diagnosis in clinical dermatology settings. This proces...

Discovery of Novel Biomarkers with Extended Non-Coding RNA Interactor Networks from Genetic and Protein Biomarkers.

International journal of molecular sciences
Curated online interaction databases and gene ontology tools have streamlined the analysis of highly complex gene/protein networks. However, understanding of disease pathogenesis has gradually shifted from a protein-based core to complex interactive ...

Image-Based Artificial Intelligence in Psoriasis Assessment: The Beginning of a New Diagnostic Era?

American journal of clinical dermatology
Psoriasis, a chronic inflammatory skin disease, affects millions of people worldwide. It imposes a significant burden on patients' quality of life and healthcare systems, creating an urgent need for optimized diagnosis, treatment, and management. In ...

Artificial intelligence in psychodermatology: A brief report of applications and impact in clinical practice.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
BACKGROUND: This report evaluates the potential of artificial intelligence (AI) in psychodermatology, emphasizing its ability to enhance diagnostic accuracy, treatment efficacy, and personalized care. Psychodermatology, which explores the connection ...

Reliable and easy-to-use calculating tool for the Nail Psoriasis Severity Index using deep learning.

NPJ systems biology and applications
Since nail psoriasis restricts the patient's daily activities, therapeutic intervention based on reliable and reproducible evaluation is critical. The Nail Psoriasis Severity Index (NAPSI) is a validated scoring tool, but its usefulness is limited by...

CAD-PsorNet: deep transfer learning for computer-assisted diagnosis of skin psoriasis.

Scientific reports
Psoriasis, being a chronic, inflammatory, lifelong skin disorder, has become a major threat to the human population. The precise and effective diagnosis of psoriasis continues to be difficult for clinicians due to its varied nature. In northern India...

Predicting psoriasis severity using machine learning: a systematic review.

Clinical and experimental dermatology
BACKGROUND: In dermatology, the applications of machine learning (ML), an artificial intelligence (AI) subset that enables machines to learn from experience, have progressed past the diagnosis and classification of skin lesions. A lack of systematic ...