Binary and Multi-label Machine Learning Models for Discrete-Time Survival Analysis: A Case Study to Predict Complications and Mortality in Thai Diabetic Patients-Reference-Cited by-同舟云学术

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Binary and Multi-label Machine Learning Models for Discrete-Time Survival Analysis: A Case Study to Predict Complications and Mortality in Thai Diabetic Patients

Published:2024-04-12 Issue: Volume:12 Page:1-7
ISSN:
Container-title:International Conference on Computing, Machine Learning and Data Science
language:
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Author:

Chheang Heng¹^ORCID,Pungpapong Vitara¹^ORCID

Affiliation:

1. Chulalongkorn University, Thailand

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3661725.3661735

Reference18 articles.

1. World Health Organization. 2023. Noncomminicable diseases. (September 2023) Retrieved September 16, 2023; from: https://www.who.int/news-room/fact-sheets/detail/noncommunicable-diseases.

2. Diabetes Prediction using Machine Learning Algorithms

3. Machine learning methods to predict diabetes complications;Dagliati Arianna;Journal of diabetes science and technology,2018

4. Yazan Jian, Michel Pasquier, Assim Sagahyroon and Fadi Aloul. 2021. A machine learning approach to predicting diabetes complications. MDPI.1712

5. Comprehensive comparative study of multi-label classification methods

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