Semantic Embedding for Medical Providers and Fraud Detection
論文傳送門 作者 佛羅里達大西洋大學 Justin M. Johnson Taghi M. Khoshgoftaar 摘要 一個醫療提供者的專業是一個重要的預測指標，可以用機器學習算法檢測出欺詐提供者。然而，當特殊變量編碼使用 one-hot 表示，模型接受稀疏和信息量不大的特徵向量。我們探討了三種技術，用於使用密集的語義嵌入表示醫療提供者類型，從而捕獲專業相似性。前兩種方法(GloVe和Med-
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相關文章
- 1. RCNN：Rich feature hierarchies for accurate object detection and semantic segmentation
- 2. Rich feature hierarchies for accurate object detection and semantic segmentation
- 3. Object Detection Network———Rcnn（Rich feature hierarchies for accurate oject detection and semantic ）
- 4. [Angular] Providers and useFactory
- 5. 論文閱讀：Associative Embedding: End-to-End Learning for Joint Detection and Grouping
- 6. Polysemous Visual-Semantic Embedding for Cross-Modal Retrieval
- 7. Medicare Fraud Detection using Machine Learning
- 8. SemEval2019Task3_ERC | (2) Attentive Conversation Modeling for Emotion Detection and Classification
- 9. 目標檢測--Rich feature hierarchies for accurate object detection and semantic segmentation(CVPR 2014)
- 10. RCNN學習筆記(1):Rich feature hierarchies for accurate object detection and semantic segmentation