Data-driven generation of medical-research hypotheses in cancer patients

Hsin Hsiung Chang, Jung Hsien Chiang, Cheng Chung Chu

研究成果: Conference contribution

摘要

Hypotheses are the most important part of medical research. If we have a good hypothesis, we can design experiments and verify it. Therefore, we use the associations generated by association rule as hypotheses in clinical medicine research. We hope this method can help physicians quickly and correctly find research hypotheses. This experiment was divided into two parts. In the first part, we used the Apriori algorithm to find associations between cancer and other catastrophic illnesses. In the second part, we used these associations as medical-research hypotheses and designed cohort studies to verify them. In this study, we proved that the association-rules method could help clinical physicians quickly and correctly obtain clinical-medicine hypotheses.

原文English
主出版物標題Proceedings - 2021 IEEE 45th Annual Computers, Software, and Applications Conference, COMPSAC 2021
編輯W. K. Chan, Bill Claycomb, Hiroki Takakura, Ji-Jiang Yang, Yuuichi Teranishi, Dave Towey, Sergio Segura, Hossain Shahriar, Sorel Reisman, Sheikh Iqbal Ahamed
發行者Institute of Electrical and Electronics Engineers Inc.
頁面626-631
頁數6
ISBN(電子)9781665424639
DOIs
出版狀態Published - 2021 7月
事件45th IEEE Annual Computers, Software, and Applications Conference, COMPSAC 2021 - Virtual, Online, Spain
持續時間: 2021 7月 122021 7月 16

出版系列

名字Proceedings - 2021 IEEE 45th Annual Computers, Software, and Applications Conference, COMPSAC 2021

Conference

Conference45th IEEE Annual Computers, Software, and Applications Conference, COMPSAC 2021
國家/地區Spain
城市Virtual, Online
期間21-07-1221-07-16

All Science Journal Classification (ASJC) codes

  • 人工智慧
  • 電腦科學應用
  • 軟體

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