{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T13:33:42Z","timestamp":1776864822935,"version":"3.51.2"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643683881","type":"print"},{"value":"9781643683898","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,5,18]],"date-time":"2023-05-18T00:00:00Z","timestamp":1684368000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,5,18]]},"abstract":"<jats:p>In medical research, the traditional way to collect data, i.e. browsing patient files, has been proven to induce bias, errors, human labor and costs. We propose a semi-automated system able to extract every type of data, including notes. The Smart Data Extractor pre-populates clinic research forms by following rules. We performed a cross-testing experiment to compare semi-automated to manual data collection. 20 target items had to be collected for 79 patients. The average time to complete one form was 6\u201981\u201d for manual data collection and 3\u201922\u201d with the Smart Data Extractor. There were also more mistakes during manual data collection (163 for the whole cohort) than with the Smart Data Extractor (46 for the whole cohort). We present an easy to use, understandable and agile solution to fill out clinical research forms. It reduces human effort and provides higher quality data, avoiding data re-entry and fatigue induced errors.<\/jats:p>","DOI":"10.3233\/shti230112","type":"book-chapter","created":{"date-parts":[[2023,5,19]],"date-time":"2023-05-19T08:43:47Z","timestamp":1684485827000},"source":"Crossref","is-referenced-by-count":4,"title":["The Smart Data Extractor, a Clinician Friendly Solution to Accelerate and Improve the Data Collection During Clinical Trials"],"prefix":"10.3233","author":[{"given":"Sophie","family":"Quennelle","sequence":"first","affiliation":[{"name":"HeKA Team, Inria Inserm UMR_S1138, PariSant\u00e9Campus, Paris, France"},{"name":"Universit\u00e9 de Paris Cit\u00e9, Paris, France"},{"name":"H\u00f4pital Universitaire Necker-Enfants malades, APHP, Paris, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maxime","family":"Douillet","sequence":"additional","affiliation":[{"name":"Data Science Platform, Imagine Institute, Paris, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lisa","family":"Friedlander","sequence":"additional","affiliation":[{"name":"Universit\u00e9 de Paris Cit\u00e9, Paris, France"},{"name":"H\u00f4pital Universitaire Necker-Enfants malades, APHP, Paris, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Olivia","family":"Boyer","sequence":"additional","affiliation":[{"name":"Universit\u00e9 de Paris Cit\u00e9, Paris, France"},{"name":"H\u00f4pital Universitaire Necker-Enfants malades, APHP, Paris, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Antoine","family":"Neuraz","sequence":"additional","affiliation":[{"name":"HeKA Team, Inria Inserm UMR_S1138, PariSant\u00e9Campus, Paris, France"},{"name":"Universit\u00e9 de Paris Cit\u00e9, Paris, France"},{"name":"H\u00f4pital Universitaire Necker-Enfants malades, APHP, Paris, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anita","family":"Burgun","sequence":"additional","affiliation":[{"name":"HeKA Team, Inria Inserm UMR_S1138, PariSant\u00e9Campus, Paris, France"},{"name":"Universit\u00e9 de Paris Cit\u00e9, Paris, France"},{"name":"H\u00f4pital Universitaire Necker-Enfants malades, APHP, Paris, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nicolas","family":"Garcelon","sequence":"additional","affiliation":[{"name":"HeKA Team, Inria Inserm UMR_S1138, PariSant\u00e9Campus, Paris, France"},{"name":"Universit\u00e9 de Paris Cit\u00e9, Paris, France"},{"name":"Data Science Platform, Imagine Institute, Paris, France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Caring is Sharing \u2013 Exploiting the Value in Data for Health and Innovation"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI230112","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,31]],"date-time":"2023-05-31T14:56:54Z","timestamp":1685545014000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI230112"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,18]]},"ISBN":["9781643683881","9781643683898"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti230112","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,5,18]]}}}