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A machine learning-based severity prediction tool for diabetic sensorimotor polyneuropathy using Michigan neuropathy screening instrumentations.

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Exploiting Weak Shape Constraints to Segment Capillary Images in Microangiopathy., , and . MICCAI, volume 1935 of Lecture Notes in Computer Science, page 717-726. Springer, (2000)A machine learning-based severity prediction tool for diabetic sensorimotor polyneuropathy using Michigan neuropathy screening instrumentations., , , , , , , , , and . CoRR, (2022)Thermal Change Index-Based Diabetic Foot Thermogram Image Classification Using Machine Learning Techniques., , , , , , , , , and 3 other author(s). Sensors, 22 (5): 1793 (2022)A machine learning model for early detection of diabetic foot using thermogram images., , , , , , , , , and . Comput. Biol. Medicine, (2021)Automatic Corneal Nerve Fibre Detection for Diabetic Neuropathy Quantification., , , , and . MIUA, page 345-350. BMVA, (2011)A Novel Machine Learning Approach for Severity Classification of Diabetic Foot Complications Using Thermogram Images., , , , , , , , , and 2 other author(s). Sensors, 22 (11): 4249 (2022)Network topology of NaV1.7 mutations in sodium channel-related painful disorders., , , , , , , , , and 27 other author(s). BMC Syst. Biol., 11 (1): 28:1-28:16 (2017)Automatic analysis of diabetic peripheral neuropathy using multi-scale quantitative morphology of nerve fibres in corneal confocal microscopy imaging., , , , and . Medical Image Anal., 15 (5): 738-747 (2011)A fully automated cell segmentation and morphometric parameter system for quantifying corneal endothelial cell morphology., , , , , , and . Comput. Methods Programs Biomed., (2018)A fully automatic nerve segmentation and morphometric parameter quantification system for early diagnosis of diabetic neuropathy in corneal images., , , , , , and . Comput. Methods Programs Biomed., (2016)