The classification of patient blood samples with machine learning techniques

Qian Deng; Jiayu Lyu; Haowen Zou

doi:10.1117/12.2673747

22 May 2023 The classification of patient blood samples with machine learning techniques

Qian Deng, Jiayu Lyu, Haowen Zou

Proceedings Volume 12640, International Conference on Internet of Things and Machine Learning (IoTML 2022); 126401I (2023) https://doi.org/10.1117/12.2673747
Event: International Conference on Internet of Things and Machine Learning (IoTML 2022), 2022, Harbin, China

Abstract

After implementing the Jaminan Kesehatan Nasional (JKN) in Indonesia, health system inequity, payment non-compliance and additional expenditure still exists. To better deal with the problems in their healthcare system, this study uses a variety of machine learning algorithms to classify patient blood samples for improving the efficiency of healthcare system. The study shows that most of the algorithms are up to 70% accuracy and the accuracy will rise with only important variables.

Citation Download Citation

Qian Deng, Jiayu Lyu, and Haowen Zou "The classification of patient blood samples with machine learning techniques", Proc. SPIE 12640, International Conference on Internet of Things and Machine Learning (IoTML 2022), 126401I (22 May 2023); https://doi.org/10.1117/12.2673747

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