{"title":"Reliable and easy-to-use calculating tool for the Nail Psoriasis Severity Index using deep learning.","authors":"Hiroto Horikawa, Keiji Tanese, Naoki Nonaka, Jun Seita, Masayuki Amagai, Masataka Saito","doi":"10.1038/s41540-024-00458-x","DOIUrl":null,"url":null,"abstract":"<p><p>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 interobserver variability. This study aimed to develop a reliable and accurate NAPSI scoring tool using deep learning. The tool \"NAPSI calculator\" includes two parts: nail detection from images and NAPSI scoring. NAPSI was annotated by nine nail experts who are board-certified dermatologists with sufficient experience in a specialized clinic for nail diseases. In the final test set, the \"NAPSI calculator\" correctly located 137/138 nails and scored NAPSI with higher accuracy than the compared six non-board-certified residents: 83.9% vs 65.7%; P = 0.008 and four board-certified non-nail expert dermatologists: 83.9% vs 73.0%; P = 0.005. The \"NAPSI calculator\" can be readily used in a clinical situation, contributing to raising the medical practice level for nail psoriasis.</p>","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"10 1","pages":"130"},"PeriodicalIF":3.5000,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11544089/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"NPJ Systems Biology and Applications","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1038/s41540-024-00458-x","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
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 interobserver variability. This study aimed to develop a reliable and accurate NAPSI scoring tool using deep learning. The tool "NAPSI calculator" includes two parts: nail detection from images and NAPSI scoring. NAPSI was annotated by nine nail experts who are board-certified dermatologists with sufficient experience in a specialized clinic for nail diseases. In the final test set, the "NAPSI calculator" correctly located 137/138 nails and scored NAPSI with higher accuracy than the compared six non-board-certified residents: 83.9% vs 65.7%; P = 0.008 and four board-certified non-nail expert dermatologists: 83.9% vs 73.0%; P = 0.005. The "NAPSI calculator" can be readily used in a clinical situation, contributing to raising the medical practice level for nail psoriasis.
期刊介绍:
npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology.
We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.