Leveraging Comprehensive Health Records for Breast Cancer Risk Prediction: A Binational Assessment.
| Autor: | Chorev M; IBM Research, Haifa, Israel., Barros V; IBM Research, Haifa, Israel.; The Hebrew University of Jerusalem, Jerusalem, Israel., Spiro A; IBM Research, Haifa, Israel., Evron E; Assuta Medical Center, Tel Aviv, Israel., Barkan E; IBM Research, Haifa, Israel., Kagan O; IBM Research, Haifa, Israel., Amit M; IBM Research, Haifa, Israel., Ozery-Flato M; IBM Research, Haifa, Israel., Akselrod-Balin A; IBM Research, Haifa, Israel., Shalev V; MaccabiTech, MKM, Maccabi Healthcare Services, Tel Aviv, Israel., Rosen-Zvi M; IBM Research, Haifa, Israel.; The Hebrew University of Jerusalem, Jerusalem, Israel., Guindy M; Assuta Medical Center, Tel Aviv, Israel. |
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| Jazyk: | angličtina |
| Zdroj: | AMIA ... Annual Symposium proceedings. AMIA Symposium [AMIA Annu Symp Proc] 2023 Apr 29; Vol. 2022, pp. 385-394. Date of Electronic Publication: 2023 Apr 29 (Print Publication: 2022). |
| Abstrakt: | Breast cancer (BC) risk models based on electronic health records (EHR) can assist physicians in estimating the probability of an individual with certain risk factors to develop BC in the future. In this retrospective study, we used clinical data combined with machine learning tools to assess the utility of a personalized BC risk model on 13,786 Israeli and 1,695 American women who underwent screening mammography in the years 2012-2018 and 2008-2018, respectively. Clinical features were extracted from EHR, personal questionnaires, and past radiologists' reports. Using a set of 1,547 features, the predictive ability for BC within 12 months was measured in both datasets and in sub-cohorts of interest. Our results highlight the improved performance of our model over previous established BC risk models, their ultimate potential for risk-based screening policies on first time patients and novel clinically relevant risk factors that can compensate for the absence of imaging history information. (©2022 AMIA - All rights reserved.) |
| Databáze: | MEDLINE |
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