Applying Machine Learning on Customized Invitation to Improve Regular Repeated Fecal Immunochemical Test and Colonoscopy Referral Rates Based on Hospital-Based Colorectal Cancer Screening

Chiu, Sherry Yueh-Hsia (PI)
Chen, Kuan-Fu (CoPI)
Kuo, Chang-Fu (CoPI)
Lin, Yung-Chang (CoPI)
Tseng, Yi-Ju (CoPI)

Project: National Science and Technology Council › National Science and Technology Council Academic Grants

Abstract

我國自2004年開始執行每兩年一次糞便潛血檢測之全國性大腸直腸癌篩檢，目前已證明大腸直腸癌晚期比例及死亡率皆呈現下降。在有限醫療人力及公衛資源下，除了維持高篩檢涵蓋率，接著將面臨定期每兩年一篩、提高陽性個案轉介率之挑戰。社會及經濟影響：將應用機器學習技術探討規律再次篩檢參與、陽性個案轉介之各別特徵分類/傾向性之預測模式建立，進一步以不同區域及不同醫療層級分析，評估手機簡訊邀約及陽性轉介簡訊提醒對於不同特徵族群之成效差異，作為未來邀約或轉介推動政策及實務執行之參考，以降低人力及資源成本。學術發展預期影響：將目前機器學習方法應用於國家癌症篩檢實務及提供給其他醫療院所運用，未來可應用於其他疾病篩檢。

Project IDs

Project ID:PC11108-0071
External Project ID:MOST109-2314-B182-038-MY3

Status	Finished
Effective start/end date	01/08/22 → 31/07/23

Keywords

Machine learning
Predictive model
Cross validation
Colorectal cancer screening
Fecal Immunochemical test (FIT)
Repeated screening
Colonoscopy referral completion rate
Text message reminder
Randomized controlled trial
Intervention
Evaluation

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https://www.grb.gov.tw/search/planDetail?id=14601721

Applying Machine Learning on Customized Invitation to Improve Regular Repeated Fecal Immunochemical Test and Colonoscopy Referral Rates Based on Hospital-Based Colorectal Cancer Screening

Project Details

Abstract

Project IDs

Keywords

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