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Development and External Validation of Machine Learning Models for Diabetic Microvascular Complications: Cross-Sectional Study With Metabolites

Development and External Validation of Machine Learning Models for Diabetic Microvascular Complications: Cross-Sectional Study With Metabolites

For people with both complications, the abovementioned characteristics further differed from those with neither complication. However, in terms of sex distribution, no significant difference was observed (P=.09). We also found differences between SEED and UKBB in terms of demographics, lifestyle factors, biochemical laboratory results, and medical history (Multimedia Appendix 4).

Feng He, Clarissa Ng Yin Ling, Simon Nusinovici, Ching-Yu Cheng, Tien Yin Wong, Jialiang Li, Charumathi Sabanayagam

J Med Internet Res 2024;26:e41065

A Patient Similarity Network (CHDmap) to Predict Outcomes After Congenital Heart Surgery: Development and Validation Study

A Patient Similarity Network (CHDmap) to Predict Outcomes After Congenital Heart Surgery: Development and Validation Study

(A) Binary postoperative complication prediction using KNN; (B) to (E) multilabel mechanical ventilation duration prediction (I: 0-12 h, II: 12-24 h, III: 24-48 h, and IV: >48 h) using KNN, respectively; (F) binary postoperative complication prediction using KNN+LR; (G) to (J) multilabel mechanical ventilation duration prediction (I: 0-12 h, II: 12-24 h, III: 24-48 h, and IV: >48 h) using KNN+LR, respectively. The performance of 3 clinicians are labeled as black stars in different tasks as C1, C2, and C3.

Haomin Li, Mengying Zhou, Yuhan Sun, Jian Yang, Xian Zeng, Yunxiang Qiu, Yuanyuan Xia, Zhijie Zheng, Jin Yu, Yuqing Feng, Zhuo Shi, Ting Huang, Linhua Tan, Ru Lin, Jianhua Li, Xiangming Fan, Jingjing Ye, Huilong Duan, Shanshan Shi, Qiang Shu

JMIR Med Inform 2024;12:e49138

Utilization of a Smart Sock for the Remote Monitoring of Patients With Peripheral Neuropathy: Cross-sectional Study of a Real-world Registry

Utilization of a Smart Sock for the Remote Monitoring of Patients With Peripheral Neuropathy: Cross-sectional Study of a Real-world Registry

Diabetic foot ulcers (DFUs) are a highly prevalent complication for people living with diabetes, who have an estimated 25% lifetime risk of developing DFUs [3]. Temperature was first identified as a predictive factor for ulceration by Benbow et al [4]. Researchers further developed temperature monitoring by measuring multiple sites on each foot to assess temperature differentials that may predict the onset of a neuropathic ulceration [5].

Henk Jan Scholten, Chia-Ding Shih, Ran Ma, Kara Malhotra, Alexander M Reyzelman

JMIR Form Res 2022;6(3):e32934