{"id":2057,"date":"2023-06-05T20:55:00","date_gmt":"2023-06-05T20:55:00","guid":{"rendered":"https:\/\/clinicaltrialrisk.org\/?p=2057"},"modified":"2023-09-02T21:41:17","modified_gmt":"2023-09-02T21:41:17","slug":"plotly-dash-challenge-webinar-on-7-june-2023","status":"publish","type":"post","link":"https:\/\/clinicaltrialrisk.org\/plotly-dash-challenge-webinar-on-7-june-2023\/","title":{"rendered":"Plotly Dash challenge webinar on 7 June, 2023"},"content":{"rendered":"\n
Natural language processing<\/a> is becoming ever more important in research. The explosion in interest in LLMs is sparking many opportunities to analyse text data in healthcare<\/a>, social sciences<\/a>, and other areas<\/a>. <\/p>\n\n\n\n We\u2019re proud to announce that the Clinical Trial Risk Tool<\/a> has been selected as a winner of the Plotly Dash Example Apps Challenge (2023)<\/a>, out of 25 amazing apps submitted by the community.<\/p>\n\n\n\n Funded by the Bill and Melinda Gates Foundation<\/a>, this app uses natural language processing<\/a>, Plotly Dash<\/a>, and the spaCy<\/a> and Scikit-Learn<\/a> libraries to calculate the risk of a clinical trial failing to deliver informative results<\/a>. It reads the trial protocol and identifies key features from the text which are fed into a risk model.<\/p>\n\n\n\n