Establishment of a differential diagnosis method and an online prediction platform for AOSD and sepsis based on gradient boosting decision trees algorithm
Abstract Objective The differential diagnosis between adult-onset Still’s disease (AOSD) and sepsis has always been a challenge. In this study, a machine learning model for differential diagnosis of AOSD and sepsis was developed and an online platform was developed to facilitate the clinical applica...
Main Authors: | Dongmei Zhou, Jingzhi Xie, Jiarui Wang, Juan Zong, Quanquan Fang, Fei Luo, Ting Zhang, Hua Ma, Lina Cao, Hanqiu Yin, Songlou Yin, Shuyan Li |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2023-11-01
|
Series: | Arthritis Research & Therapy |
Subjects: | |
Online Access: | https://doi.org/10.1186/s13075-023-03207-3 |
Similar Items
-
18F-FDG PET/CT Associates With Disease Activity and Clinical Recurrence of AOSD Patients
by: Xian Li, et al.
Published: (2021-05-01) -
A boosting ensemble learning based hybrid light gradient boosting machine and extreme gradient boosting model for predicting house prices
by: Racheal Sibindi, et al.
Published: (2023-04-01) -
Plasma microRNA Profiles as a Potential Biomarker in Differentiating Adult-Onset Still's Disease From Sepsis
by: Qiongyi Hu, et al.
Published: (2019-01-01) -
Sequential Training of Neural Networks With Gradient Boosting
by: Seyedsaman Emami, et al.
Published: (2023-01-01) -
Gradient boosted graph convolutional network on heterophilic graph
by: Seah, Ming Yang
Published: (2024)