{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T11:48:57Z","timestamp":1791287337291,"version":"4.1.0"},"reference-count":9,"publisher":"S. Karger AG","issue":"2","license":[{"start":{"date-parts":[[2009,1,1]],"date-time":"2009-01-01T00:00:00Z","timestamp":1230768000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.karger.com\/Services\/SiteLicenses"},{"start":{"date-parts":[[2009,1,1]],"date-time":"2009-01-01T00:00:00Z","timestamp":1230768000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.karger.com\/Services\/SiteLicenses"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Dermatology"],"published-print":{"date-parts":[[2009]]},"abstract":"<jats:p>&lt;i&gt;Background:&lt;\/i&gt; A predictive model may help to select likely responders and to anticipate treatment duration in vitiligo. &lt;i&gt;Methods:&lt;\/i&gt; We aimed to develop a predictive rule based on data from a randomized trial of excimer laser in vitiligo. Information on 325 treated patches was available. The degree of repigmentation was assessed by digital image analysis of UVB-reflected photographs. Since no strong relationship between any single predictive parameter and outcome was initially documented, we relied on artificial neural networks. &lt;i&gt;Results:&lt;\/i&gt; Using a time-response optimal threshold model, data were divided into 2 groups of responders and nonresponders. A discriminant network was trained in order to detect responders versus nonresponders. A regression network was subsequently used to compute repigmentation time in responders. The neural network discriminator achieved 66.46 \u00b1 5.37% (95% CI) overall accuracy. The mean absolute error of the neural network regressor was 19.5843 \u00b1 2.0930 with a root mean square error of 23.7156 \u00b1 2.2225. &lt;i&gt;Conclusion:&lt;\/i&gt; Our study offers insight into the difficulty of clinical prediction in vitiligo and presents a way to develop an instrument with which to predict the clinical time response in patients treated by excimer laser.<\/jats:p>","DOI":"10.1159\/000225934","type":"journal-article","created":{"date-parts":[[2009,6,18]],"date-time":"2009-06-18T07:35:22Z","timestamp":1245310522000},"page":"133-137","source":"Crossref","is-referenced-by-count":25,"title":["Prediction of Clinical Response to Excimer Laser Treatment in Vitiligo by Using Neural Network Models"],"prefix":"10.1159","volume":"219","author":[{"given":"Simone","family":"Cazzaniga","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fabrizia","family":"Sassi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Santo Raffaele","family":"Mercuri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luigi","family":"Naldi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"127","published-online":{"date-parts":[[2009,6,18]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016%2FS0190-9622%2896%2990112-7"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1001%2Farchderm.135.12.1514"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1001%2Farchderm.143.5.643"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1001%2Farchderm.138.12.1619"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1162%2Fneco.1992.4.3.415"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1162%2Fneco.1992.4.3.448"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016%2FS0893-6080%2803%2900116-3"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1093%2Fbiomet%2F92.3.529"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016%2Fj.jaad.2006.09.004"}],"container-title":["Dermatology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.karger.com\/Article\/Pdf\/225934","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.karger.com\/Article\/Pdf\/225934","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,23]],"date-time":"2025-04-23T22:59:34Z","timestamp":1745449174000},"score":1,"resource":{"primary":{"URL":"https:\/\/karger.com\/article\/doi\/10.1159\/000225934"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2009]]},"references-count":9,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2009,8,1]]}},"URL":"https:\/\/doi.org\/10.1159\/000225934","archive":["Portico"],"relation":{},"ISSN":["1018-8665","1421-9832"],"issn-type":[{"value":"1018-8665","type":"print"},{"value":"1421-9832","type":"electronic"}],"subject":[],"published":{"date-parts":[[2009]]}}}