Yingzhi Li
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An interpretable machine learning model for diabetic foot risk classification in patients with diabetes
Abstract Diabetic foot is a severe chronic complication of diabetes, mainly resulting from peripheral neuropathy and vasculopathy, and may progress to ulcers, infections, and amputation if not treated in a timely manner. Early identification of patients who already present a high-risk diabetic foot profile at clinical evaluation is therefore critical for guiding preventive interventions.
Parallel 4D Solid‐State LiDAR Enabled by an Integrated Si‐SiN Focal Plane Switch Array Chip
Conflicts of Interest The authors declare no conflicts of interest. Data Availability Statement The data that support the fundings of this study are available from the corresponding author upon reasonable request. Supporting Information Filename Description lpor71008-sup-0001-SuppMat.docx1.6 MB Supporting File: lpor71008-sup-0001-SuppMat.docx References 1, , , , and , “Photonic Technologies for Autonomous Cars: Feature Introduction,” Optics Express 27, no.
A dual oscillatory particle swarm optimization for tomato disease classification
A dual oscillatory particle swarm optimization for tomato disease classification 1Faculty of Information Science and Technology, Wenhua College, Wuhan, Hubei, China 2Faculty of Computer and Information Sciences, Hosei University, Tokyo, Japan 3School of Information Engineering, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou, China 4Hubei Key Laboratory of Digital Finance Innovation (Hubei University of Economics), Wuhan, Hubei, China...
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