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RSSDI Repository, Complications of Diabetes Demonstration

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Usability Evaluation and Classification of mHealth Applications for Type 2 Diabetes Mellitus Using MARS and ID3 Algorithm.

Keywords : ["type diabetes mellitus use mar", "usability evaluation", "mhealth application", "classification", "algorithm"]
Author : K Gupta
55

Usability Evaluation and Classification of mHealth Applications for Type 2 Diabetes Mellitus Using MARS and ID3 Algorithm.

Keywords : ["type diabetes mellitus use mar", "usability evaluation", "mhealth application", "classification", "algorithm"]
Author : K Gupta
53

Machine learning algorithm to evaluate risk factors of diabetic foot ulcers and its severity.

Keywords : ["machine learn algorithm", "evaluate risk factor", "diabetic foot ulcer", "severity"]
Author : R Nanda
66

Machine learning algorithm to evaluate risk factors of diabetic foot ulcers and its severity.

Keywords : ["machine learn algorithm", "evaluate risk factor", "diabetic foot ulcer", "severity"]
Author : R Nanda
55

Characteristics of children and adolescents with newly diagnosed Fibrocalculous pancreatitis diabetes (FCPD) and type 1 diabetes: A study from Eastern India.

Keywords : ["newly diagnose fibrocalculous pancreatitis diabetes fcpd", "type diabetes", "eastern india", "study", "child", "characteristic", "adolescent"]
Author : D Sanyal
37

Novel Topical Esmolol Hydrochloride (Galnobax) for Diabetic Foot Wound: Phase 1/2, Multicenter, Randomized, Double-Blind, Vehicle-Controlled Parallel-Group Study.

Keywords : ["diabetic foot wound phase multicenter randomize doubleblind vehiclecontrolled parallelgroup study", "novel topical esmolol hydrochloride galnobax"]
Author : A Rastogi
104

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Usability Evaluation and Classification of mHealth Applications for Type 2 Diabetes Mellitus Using MARS and ID3 Algorithm.

Usability Evaluation and Classification of mHealth Applications for Type 2 Diabetes Mellitus Using MARS and ID3 Algorithm.

Machine learning algorithm to evaluate risk factors of diabetic foot ulcers and its severity.

Machine learning algorithm to evaluate risk factors of diabetic foot ulcers and its severity.

Characteristics of children and adolescents with newly diagnosed Fibrocalculous pancreatitis diabetes (FCPD) and type 1 diabetes: A study from Eastern India.

Development of pharmacogenomic algorithm to optimize nateglinide dose for the treatment of type 2 diabetes mellitus.

Development of pharmacogenomic algorithm to optimize nateglinide dose for the treatment of type 2 diabetes mellitus.

Diabetic retinopathy screening using deep learning for multi-class imbalanced datasets.

Artificial Humming Bird Optimization-Based Hybrid CNN-RNN for Accurate Exudate Classification from Fundus Images.

Novel Topical Esmolol Hydrochloride (Galnobax) for Diabetic Foot Wound: Phase 1/2, Multicenter, Randomized, Double-Blind, Vehicle-Controlled Parallel-Group Study.