{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/70fb5b77a5ea4221b25fca637da47a3e\" frameborder=\"0\" width=\"1990\" height=\"1492\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1492,"width":1990,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1492,"thumbnail_width":1990,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/70fb5b77a5ea4221b25fca637da47a3e-b0a8510f87e7f37c.gif","duration":561.64,"title":"TrialMatch AI Clinical Trial Eligibility Screener Demo","description":"This Loom demonstrates TrialMatch AI, a clinical trial eligibility screener that matches patients to oncology protocols in minutes. It explains that only about 5% of cancer patients enroll in trials while around 80% of trials fall behind, and that current matching requires manual line-by-line review of 40 to 80 page protocols. The presenter uploads a real xCure protocol PDF and screens four patient scenarios, showing eligible outcomes with per-criterion rationales, geographic ineligibility for patients not getting care in the U.S., a need-review result for insufficient data when biopsy confirmation is missing, and an eligibility edge case using a legally authorized representative for a 9-year-old. The tool is presented as not using protocol-invented thresholds and as flagging when data is unclear."}