EICHORCondition: Breast Cancer · Sponsor: Cancer Institute and Hospital, Chinese Academy of Medical Sciences
Sponsor, CRO or site team? See where this study is running → — listed sites, countries and recruiting context. Everything below is written for patients and caregivers.
Breast cancer has become the world's number one cancer. While its therapeutic efficacy is increasing, how to achieve non-invasive evaluation of the efficacy of neoadjuvant therapy (NAT) for breast cancer patients and thus avoid surgery has become a bottleneck problem that needs to be broken through in clinical diagnosis and treatment. Existing non-invasive evaluation strategies are limited to single-center, single-modality modeling, and have problems such as low performance and poor versatility. Therefore, in the early stage of this study, multi-modality breast cancer patient data from multiple centers across the country were collected and the establishment of an artificial intelligence (AI) efficacy prediction model was preliminarily completed. On this basis, this project intends to further improve the multi-center prospective validation study of the prediction model. The research results will help solve the scientific problem of non-invasive judgment of NAT efficacy in breast cancer patients and provide a new paradigm for the research of high-performance AI diagnosis and treatment auxiliary systems applicable to multiple centers.
This description comes directly from the study's public registry record.
peng yuan, doctor · 01087787242 · yuanpengyp01@163.com
Always discuss trial participation with your own doctor first.
| Sanhuan Cancer Hospital, Chaoyang District, Beijing(Cancer Hospital, Chinese Academy of Medical Sciences, close medical alliance) | Beijing, Beijing Municipality, China | Recruiting |
| Cancer Hospital, Chinese Academy of Medical Sciences | Beijing, Beijing Municipality, China | Recruiting |
Get one email when the public record changes — results posted, or the study's status changes. Nothing else, ever.
We email about this public record only. Unsubscribe anytime with one click. Never medical advice. By subscribing you agree to our Terms of Use and Privacy Policy.
This page is independently generated by Eichor from the public ClinicalTrials.gov record and re-synced daily. It is not the sponsor's official website unless claimed. Nothing here is medical advice; eligibility is always determined by the study team — talk to your own doctor first.
Source record: clinicaltrials.gov/study/NCT06649565