An interpretable machine learning model for diabetic foot risk classification in patients with diabetes
X
Xiaohua Hu
(State Key Laboratory of Marine Environmental Science, Xiamen University)
H
Huijun Xi
Z
Zibo Fan
L
Leixia Zhu
J
Jia Shi
(State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering & Institute of Artificial Intelligence & Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM))
S
Shuangshuang Qian
J
Jing Qiu
Y
Yingzhi Li
H
Hong Ding
(Tsung-Dao Lee Institute, School of Physics and Astronomy, and State Key Laboratory of Micro-nano Engineering Science, Shanghai Jiao Tong University, Shanghai, China.)
Article Details
Journal
Scientific Reports
Volume / Issue
Vol. 1, Issue 1
Published
June 23, 2026
ISSN
2045-2322
Publisher
Nature Portfolio
Authors (9)
X
Xiaohua Hu
State Key Laboratory of Marine Environmental Science, Xiamen University
H
Huijun Xi
Z
Zibo Fan
L
Leixia Zhu
J
Jia Shi
State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering & Institute of Artificial Intelligence & Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM)
S
Shuangshuang Qian
J
Jing Qiu
Y
Yingzhi Li
H
Hong Ding
Tsung-Dao Lee Institute, School of Physics and Astronomy, and State Key Laboratory of Micro-nano Engineering Science, Shanghai Jiao Tong University, Shanghai, China.
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