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    "description": "Data Set Information:\nThis has been collected using direct questionnaires from the patients of Sylhet Diabetes\nHospital in Sylhet, Bangladesh and approved by a doctor.\nData Set Information:\nThis has been col-\nlected using direct questionnaires from the patients of Sylhet Diabetes\nHospital in Sylhet, Bangladesh and approved by a doctor.\nAttribute Information:\nAge 1.20-65\nSex 1. Male, 2.Female\nPolyuria 1.Yes, 2.No.\nPolydipsia 1.Yes, 2.No.\nsudden weight loss 1.Yes, 2.No.\nweakness 1.Yes, 2.No.\nPolyphagia 1.Yes, 2.No.\nGenital thrush 1.Yes, 2.No.\nvisual blurring 1.Yes, 2.No.\nItching 1.Yes, 2.No.\nIrritability 1.Yes, 2.No.\ndelayed healing 1.Yes, 2.No.\npartial paresis 1.Yes, 2.No.\nmuscle stiness 1.Yes, 2.No.\nAlopecia 1.Yes, 2.No.\nObesity 1.Yes, 2.No.\nClass 1.Positive, 2.Negative.\nRelevant Papers:\nLikelihood Prediction of Diabetes at Early Stage Using Data Mining Techniques\n[Web Link]\nAuthors and affiliations\nM. M. Faniqul IslamEmail\nRahatara Ferdousi\nSadikur Rahman\nHumayra Yasmin Bushra\nCitation Request:\nIslam, MM Faniqul, et al. 'Likelihood prediction of diabetes at early stage using data mining techniques.' Computer Vision and Machine Intelligence in Medical Image Analysis. Springer, Singapore, 2020. 113-125.\nIslam, MM Faniqul, et al. 'Likelihood prediction of diabetes at early stage using data mining techniques.' Computer Vision and Machine Intelligence in Medical Image Analysis. Springer, Singapore, 2020. 113-125.",
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