Tunghai University

Taichung Veterans General Hospital

Shang-Feng Tsai

Chien-Chung Huang

Chieh-Liang Wu

Chien-Lun Liao

Min-Shian Wang

Ruey-Kai Sheu

Kai-Chih Pai

Yan-Nan Lin

Lun-Chi Chen

Ta-Chun Hung

Chia-Tien Hsu

Tsai-Jung Wang

Chun-Ming Lai

Cheng-Hsu Chen

Chun-Te Huang

An acute kidney injury predicting system and a method thereof are proposed. A processor reads the data to be tested, the detection data, the machine learning algorithm and the risk probability comparison table from a main memory. The processor trains the detection data according to the machine learning algorithm to generate an acute kidney injury prediction model, and inputs the data to be tested into the acute kidney injury prediction model to generate an acute kidney injury characteristic risk probability and a data sequence table. The data sequence table lists the data to be tested in sequence according to a proportion of each of the data to be tested in the acute kidney injury characteristics. The processor selects one of the medical treatment data from the risk probability comparison table according to the acute kidney injury characteristic risk probability.

Acute kidney injury predicting system and method thereof

Growing community of inventors

Taichung, Taiwan

Shang-Feng Tsai