Enhancing Cognitive Frailty Prediction Accuracy Using Conditional Generative Adversarial Networks(CGAN)
Class imbalance is a prevalent issue in real-life scenarios, especially in medical datasets where instances of normal health conditions far outnumber those with health conditions, for example, Cognitive Frailty. This imbalance can lead to predictive models biased towards the majority class, thus dim...
| 出版年: | ACM International Conference Proceeding Series |
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| 第一著者: | |
| フォーマット: | Conference paper |
| 言語: | English |
| 出版事項: |
Association for Computing Machinery
2024
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| オンライン･アクセス: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215947639&doi=10.1145%2f3702138.3702151&partnerID=40&md5=7a185588287fc31fdccf1004508663f7 |