Prediction of Prognostic Risk Factors in Patients with Invasive Candidiasis and Cancer: A Single-Centre Retrospective Study.

Jingyi Li Yaling Li Yali Gao Xueli Niu Mingsui Tang Chang Fu Zihan Wang Jiayi Liu Bing Song Hong-Duo Chen Xing-Hua Gao Xiuhao Guan

Published in: BioMed research international (2022)

In this study, the machine learning-based models accurately predicted the prognosis of cancer and invasive candidiasis patients. The algorithm could be used to help clinicians in high-risk patients' early intervention.

Keyphrases

machine learning
end stage renal disease
risk factors
ejection fraction
chronic kidney disease
newly diagnosed
randomized controlled trial
prognostic factors
papillary thyroid
squamous cell carcinoma
deep learning
young adults
artificial intelligence
squamous cell