scholarly journals What's in a Name? Classification of Diabetes Mellitus in Veterinary Medicine and Why It Matters

2016 ◽  
Vol 30 (4) ◽  
pp. 927-940 ◽  
Author(s):  
C. Gilor ◽  
S.J.M. Niessen ◽  
E. Furrow ◽  
S.P. DiBartola
Keyword(s):  
Diabetes Mellitus ◽  
Veterinary Medicine

Functional Link Convolutional Neural Network for the Classification of Diabetes Mellitus

2021 ◽  
Author(s):  
Sunil Kumar Jangir ◽  
Nakul Joshi ◽  
Manish Kumar ◽  
Dilip Kumar Choubey ◽  
Shatakshi Singh ◽  
...  
Keyword(s):  
Neural Network ◽  
Diabetes Mellitus ◽  
Convolutional Neural Network ◽  
Functional Link

The challenges of diagnosing diabetes in childhood

Diagnosis ◽  
2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Mairi Pucci ◽  
Marco Benati ◽  
Claudia Lo Cascio ◽  
Martina Montagnana ◽  
Giuseppe Lippi
Keyword(s):  
Diabetes Mellitus ◽  
Children And Young People ◽  
Narrative Literature ◽  
Diagnosis And Classification ◽  
Narrative Literature Review ◽  
Optimal Approach ◽  
Diagnostic Step

AbstractDiabetes is one of the most prevalent diseases worldwide, whereby type 1 diabetes mellitus (T1DM) alone involves nearly 15 million patients. Although T1DM and type 2 diabetes mellitus (T2DM) are the most common types, there are other forms of diabetes which may remain often under-diagnosed, or that can be misdiagnosed as being T1DM or T2DM. After an initial diagnostic step, the differential diagnosis among T1DM, T2DM, Maturity-Onset Diabetes of the Young (MODY) and others forms has important implication for both therapeutic and behavioral decisions. Although the criteria used for diagnosing diabetes mellitus are well defined by the guidelines of the American Diabetes Association (ADA), no clear indications are provided on the optimal approach to be followed for classifying diabetes, especially in children. In this circumstance, both routine and genetic blood test may play a pivotal role. Therefore, the purpose of this article is to provide, through a narrative literature review, some elements that may aid accurate diagnosis and classification of diabetes in children and young people.

scholarly journals Evaluation of the new ADA and WHO criteria for classification of diabetes mellitus in young adult people (15?34 yrs) in the Diabetes Incidence Study in Sweden (DISS)

Diabetologia ◽  
2004 ◽  
Vol 47 (1) ◽  
pp. 154-154
Author(s):  
H. Borg ◽  
H. J. Arnqvist ◽  
E. Bj�rk ◽  
J. Bolinder ◽  
J. W. Eriksson ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Young Adult ◽  
Incidence Study ◽  
Diabetes Incidence ◽  
Who Criteria

Classification of Diabetes Mellitus using Ensemble Algorithms

2021 ◽  
Author(s):  
Noor Azmiya Bt Sirajun Noor ◽  
Irraivan Elamvazuthi ◽  
Norashikin Yahya
Keyword(s):  
Diabetes Mellitus ◽  
Ensemble Algorithms

Comparative approaches for classification of diabetes mellitus data: Machine learning paradigm

2017 ◽  
Vol 152 ◽  
pp. 23-34 ◽  
Author(s):  
Md. Maniruzzaman ◽  
Nishith Kumar ◽  
Md. Menhazul Abedin ◽  
Md. Shaykhul Islam ◽  
Harman S. Suri ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Machine Learning ◽  
Learning Paradigm

scholarly journals Ultrasonography in diagnosis of sexual development delay of girls and teenagers having diabetes mellitus of the 1st type

2002 ◽  
Vol 1 (4) ◽  
pp. 87-92
Author(s):  
N. M. Kondratyeva ◽  
V. D. Zavadovskaya ◽  
E. B. Kravets ◽  
E. V. Gorbatenko ◽  
L. S. Strelis
Keyword(s):  
Diabetes Mellitus ◽  
Blood Flow ◽  
Sexual Development ◽  
The Body ◽  
Ultrasound Studies ◽  
Ultrasound Study ◽  
Development Delay ◽  
The Given ◽  
Ultrasound Classification

Girls-teenagers (n = 85) aged from 8 to 18 years having diabetes mellitus (DM) of the 1st type were investigated using ultrasonography method. Based upon decreasing and disproportion of the body and neck of the uterus, changed Mecho thickness and ovaries structure, different parameter of blood flow, we worked out classification of the four stages of sexual development delay (SDD) (0 stage in 15 girls, I stage in 26 girls, II stage in 20 girls and III stage in 21 girls). Comparative analysis of clinical and ultrasound studies showed the advantage of ultrasound study to assess status of internal genital organs in girls and teenagers having DM. Investigation performed based upon E. Tanner classification revealed SDD 40 girls, bimanual examination in 45 girls, sonography method — in 82 girls. The given ultrasound classification of sexual development delay in girls-teenagers having DM of the 1st type contributes to diagnosis and prescribing timely effective correction therapy.

scholarly journals PATHYAPATHYA IN PRAMEHA

2021 ◽  
Vol 9 (8) ◽  
pp. 1806-1814
Author(s):  
Ripsa Raj K. P ◽  
P Sudhakar Reddy
Keyword(s):  
Diabetes Mellitus ◽  
Scientific Explanation ◽  
Medical Science ◽  
Great Influence ◽  
Clinical Entity ◽  
Causative Factors ◽  
The World ◽  
Growing Population

Diabetes mellitus is becoming the fastest considerable disease in the world. India has been estimated with the fast- est-growing population of Diabetics. According to International Diabetic Federation (IDF), the total number of Diabetic subjects will be around 151 million in India by 2045. The clinical entity of Prameha can be correlated with Diabetes Mellitus. It is considered a Lifestyle disorder, the food, drinks and sedentary habits are having a great influence on this disorder. In Ayurveda classics elaborately mentioned the Nidana (causative factors) and Pathya ahara (wholesome food & drinks) and Apathya ahara (unwholesome food & drinks), Pathya Vihara (Conducive lifestyle) and Apathya Vihara (Non-Conducive lifestyle) of Prameha. The classification of Prameha as per Susruta Samhita as Apathya nimittaja Prameha and Beeja doshaja Prameha indicates the importance of Ahara and Vihara in prevention as well as management of this disease. In this article, a sincere attempt has been made to incorporate the principles of Ayurveda and Modern medical science with a scientific explanation regarding Pathya (Diet) and Vihara (lifestyle) in Prameha (Diabetes Mellitus). Keywords: Pathya, Apathya, Prameha, Ahara, Vihara.

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