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Linear decision fusions in multilayer perceptrons for breast cancer diagnosis

  • Yunfeng Wu
  • , Jinming Zhang
  • , Cong Wang
  • , Sin Chun Ng

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

10 Citations (Scopus)

Abstract

We Introduce a non-parametric linear decision fusion called Perceptron Average (PA) for breast cancer diagnosis. We concretely compare the accuracy between both two fusion strategies for breast cancer diagnosis, The PA fusion demonstrates a higher overall diagnostic accuracy versus the Weighted Average fusion, and the PA fusion method also exhibits a better capability of generalization when a casualty of training data sizes. Moreover, the PA fusion gains a larger area covered by its Receiver Operating Characteristic curve.

Original languageEnglish
Title of host publicationICTAI 2005
Subtitle of host publication17th IEEE International Conference on Tools with Artificial Intelligence, ICTAI'05
Pages698-700
Number of pages3
DOIs
Publication statusPublished - 2005
EventICTAI 2005: 17th IEEE International Conference on Tools with Artificial Intelligence, ICTAI'05 - Hong Kong, China
Duration: 14 Nov 2005 → 16 Nov 2005

Publication series

NameProceedings - International Conference on Tools with Artificial Intelligence, ICTAI
Volume2005
ISSN (Print)1082-3409

Conference

ConferenceICTAI 2005: 17th IEEE International Conference on Tools with Artificial Intelligence, ICTAI'05
Country/TerritoryChina
CityHong Kong
Period14/11/05 → 16/11/05

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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