Mathematical Model for Early Diagnosis of Diabetes Mellitus

Author(s):  
Indira Uvaliyeva ◽  
Aigerim Ismukhamedova
2019 ◽  
Vol 8 (3) ◽  
Author(s):  
Seyed Ataaldin Mahmoudinejad Dezfuli ◽  
Seyedeh Razieh Mahmoudinejad Dezfuli ◽  
Seyed Vafaaldin Mahmoudinejad Dezfuli ◽  
Younes Kiani

Author(s):  
Humaidillah Kurniadi Wardana ◽  
Imamatul Ummah ◽  
Lina Arifah Fitriyah

Diabetes Mellitus (DM) is one of the deadliest degenerative diseases in the world. The prevalence of DM in Indonesia from year to year shows asignificant increase. The high number of these causes the need for appropriate action and anticipation for health workers, DM families and DM people themselves. In this study, a system application model was created by using informatics techniques in health for early diagnosis of DM and what calorie needs needed for DM sufferers. This system was created using a GUI application and the Mamdani fuzzy method. The purpose of creating this system is to help in making an initial decision for DM diagnosis. The results obtained, first a DM diagnosis system with 6 input variables, 3 output variables, and 155 rules with MAPE achieved 29.48%. The second is the calorie requirements system with 2 input variables, 2 output variables namely BMI with MAPE 10.57% BMR with MAPE 9.7% and 9 rules with the results achieved by 99%.


2021 ◽  
Vol 11 (6) ◽  
pp. 13-14
Author(s):  
Jayanthi Bai ◽  
Jayakrishnan .

Early diagnosis of diabetes is clinically important in reducing health complications worldwide. In this respect HbA1c has become an accurate biomarker for the diagnosis of Diabetes Mellitus (DM) and its complication [1]. In the present study HbA1c measured in subject of age <20,21-30,31-40 yrs and the level found to show high risk for DM in youngsters. Hence counselling at least once a month is warranted. To be most effective to reduce or prevent the prevalence in youngsters the importance of controlling HbA1c and keeping it at low level can be achieved by including in the curriculum right from school ageing. It will reduce the financial burden on state and central government authorities. Key words: HbA1c, Diabetes Mellitus 2.


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