Transfer Learning for Early Prediction of Adverse Drug Reactions: Docetaxel and Alopecia in Breast Cancer as a Case Study

被引：1

作者：

Dimitsaki, Stella ^{[1
,2
]}

Natsiavas, Pantelis ^{[2
]}

Jaulent, Marie-Christine ^{[1
]}

机构：

[1] Univ Paris 13, Sorbonne Univ, INSERM, LIMICS, F-75006 Paris, France

[2] Ctr Res & Dev Hellas, Inst Appl Biosci, Thessaloniki, Greece

来源：

CARING IS SHARING-EXPLOITING THE VALUE IN DATA FOR HEALTH AND INNOVATION-PROCEEDINGS OF MIE 2023 | 2023年 / 302卷

关键词：

Breast cancer; docetaxel; adverse drug reaction; alopecia; transfer learning;

D O I：

10.3233/SHTI230158

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Transfer Learning (TL) is an approach which has not yet been widely investigated in healthcare, mostly applied in image data. This study outlines a TL pipeline leveraging Individual Case Safety reports (ICSRs) and Electronic Health Records (EHR), applied for the early detection Adverse Drug Reactions (ADR), evaluated using of alopecia and docetaxel on breast cancer patients as use case.

引用

页码：396 / 397

页数：2

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