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  • Open Access


    Hybrid Online Model for Predicting Diabetes Mellitus

    C. Mallika1,*, S. Selvamuthukumaran2

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1873-1885, 2022, DOI:10.32604/iasc.2022.020543

    Abstract Modern healthcare systems have become smart by synergizing the potentials of wireless sensors, the medical Internet of things, and big data science to provide better patient care while decreasing medical expenses. Large healthcare organizations generate and accumulate an incredible volume of data continuously. The already daunting volume of medical information has a massive amount of diagnostic features and logged details of patients for certain diseases such as diabetes. Diabetes mellitus has emerged as along-haul fatal disease across the globe and particularly in developing countries. Exact and early diagnosis of diabetes from big medical data is vital for the deterrence of… More >

  • Open Access


    Deep Learning Model to Detect Diabetes Mellitus Based on DNA Sequence

    Noha E. El-Attar1,*, Bossy M. Moustafa2, Wael A. Awad3

    Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 325-338, 2022, DOI:10.32604/iasc.2022.019970

    Abstract DNA sequence classification is considered a significant challenge for biological researchers to scientifically analyze the enormous volumes of biological data and discover different biological features. In genomic research, classifying DNA sequences may help learn and discover the new functions of a protein. Insulin is an example of a protein that the human body produces to regulate glucose levels. Any mutations in the insulin gene sequence would result in diabetes mellitus. Diabetes is one of the widely spread chronic diseases, leading to severe effects in the longer term if diagnosis and treatment are not appropriately taken. In this research, the authors… More >

  • Open Access


    Ensemble Classifier Technique to Predict Gestational Diabetes Mellitus (GDM)

    A. Sumathi*, S. Meganathan

    Computer Systems Science and Engineering, Vol.40, No.1, pp. 313-325, 2022, DOI:10.32604/csse.2022.017484

    Abstract Gestational Diabetes Mellitus (GDM) is an illness that represents a certain degree of glucose intolerance with onset or first recognition during pregnancy. In the past few decades, numerous investigations were conducted upon early identification of GDM. Machine Learning (ML) methods are found to be efficient prediction techniques with significant advantage over statistical models. In this view, the current research paper presents an ensemble of ML-based GDM prediction and classification models. The presented model involves three steps such as preprocessing, classification, and ensemble voting process. At first, the input medical data is preprocessed in four levels namely, format conversion, class labeling,… More >

  • Open Access


    Deep Learning Based Process Analytics Model for Predicting Type 2 Diabetes Mellitus

    A. Thasil Mohamed, Sundar Santhoshkumar*

    Computer Systems Science and Engineering, Vol.40, No.1, pp. 191-205, 2022, DOI:10.32604/csse.2022.016754

    Abstract Process analytics is one of the popular research domains that advanced in the recent years. Process analytics encompasses identification, monitoring, and improvement of the processes through knowledge extraction from historical data. The evolution of Artificial Intelligence (AI)-enabled Electronic Health Records (EHRs) revolutionized the medical practice. Type 2 Diabetes Mellitus (T2DM) is a syndrome characterized by the lack of insulin secretion. If not diagnosed and managed at early stages, it may produce severe outcomes and at times, death too. Chronic Kidney Disease (CKD) and Coronary Heart Disease (CHD) are the most common, long-term and life-threatening diseases caused by T2DM. Therefore, it… More >

  • Open Access


    An Intelligent Gestational Diabetes Diagnosis Model Using Deep Stacked Autoencoder

    A. Sumathi1,*, S. Meganathan1, B. Vijila Ravisankar2

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3109-3126, 2021, DOI:10.32604/cmc.2021.017612

    Abstract Gestational Diabetes Mellitus (GDM) is one of the commonly occurring diseases among women during pregnancy. Oral Glucose Tolerance Test (OGTT) is followed universally in the diagnosis of GDM diagnosis at early pregnancy which is costly and ineffective. So, there is a need to design an effective and automated GDM diagnosis and classification model. The recent developments in the field of Deep Learning (DL) are useful in diagnosing different diseases. In this view, the current research article presents a new outlier detection with deep-stacked Autoencoder (OD-DSAE) model for GDM diagnosis and classification. The goal of the proposed OD-DSAE model is to… More >

  • Open Access


    Cell proliferation of the ileum intestinal mucosa of diabetic rats treated with ascorbic acid


    BIOCELL, Vol.32, No.2, pp. 163-168, 2008, DOI:10.32604/biocell.2008.32.163

    Abstract The objective of this work was to evaluate the effect of the ascorbic acid supplementation on the cellular proliferation on the ileum mucosa of diabetic rats. Fifteen 90-days rats were divided in the groups: control, diabetic and diabetic supplemented with ascorbic acid (DA). Two hours prior the sacrifice, they were injected with Vincristin. Semi-seriate histological cuts stained with HE were accomplished. About 2500 crypt cells from the intestinal mucosa were counted in order to obtain the metaphasic indexes. The height and depth of 30 villi and 30 crypts were measured for each animal, respectively. The metaphasic indexes showed no significant… More >

  • Open Access


    Effects of the ascorbic acid supplementation on NADH-diaphorase myenteric neurons in the duodenum of diabetic rats


    BIOCELL, Vol.30, No.2, pp. 295-300, 2006, DOI:10.32604/biocell.2006.30.295

    Abstract We assessed the ascorbic acid (AA) supplementation on the myenteric neurons in the duodenum of rats. Fifteen rats with 90 days of age were divided into three groups: control (C), diabetics (D) and ascorbic acid treated diabetics (DA). After 120 days of daily treatment with AA, the duodenum was submitted to the NADH-diaphorase (NADH-d) histochemical technique, which allowed us to evaluate the neuronal density in an area of 8.96 mm2 for each duodenum, and also to measure the cellular profile area of 500 neurons per group. The supplementation promoted an increase on AA levels. The neuronal density (p <0.05) was… More >

  • Open Access


    Tubulointerstitial injury and proximal tubule albumin transport in early diabetic nephropathy induced by type 1 diabetes mellitus

    Maximiliano GIRAUD-BILLOUD1, 2*, Fernando EZQUER2, Javiera BAHAMONDE2, Marcelo EZQUER2

    BIOCELL, Vol.41, No.1, pp. 1-12, 2017, DOI:10.32604/biocell.2017.41.001

    Abstract A decrease in the tubular expression of albumin endocytic transporters megalin and cubilin has been associated with diabetic nephropathy, but there are no comprehensive studies to date relating early tubulointerstitial injury and the effect of the disease on both transporters in type 1 diabetes mellitus (T1DM). We used eight-weekold male C57BL/6 mice divided into two groups; one of them received the vehicle (control group), while the other received the vehicle + 200 mg/kg streptozotocin (T1DM). Ten weeks after the injection, we evaluated plasma insulin, enzymuria, urinary vitamin D-binding protein (VDBP), tubulointerstitial fibrosis and proximal tubule histology, markers of autophagy, and… More >

  • Open Access


    Diabetic nephropathy, autophagy and proximal tubule protein endocytic transport: A potentially harmful relationship

    Maximiliano GIRAUD-BILLOUD1,2,*, Claudio M. FADER1,3, Rocío AGÜERO2, Fernando EZQUER4, Marcelo EZQUER4

    BIOCELL, Vol.42, No.2, pp. 35-40, 2018, DOI:10.32604/biocell.2018.07010

    Abstract Diabetic nephropathy (DN) is the most frequent cause of chronic renal failure. Until now, the pathophysiological mechanisms that determine its development and progression have not yet been elucidated. In the present study, we evaluate the role of autophagy at early stages of DN, induced in type 2 diabetes mellitus (T2DM) mouse, and its association with proximal tubule membrane endocytic receptors, megalin and cubilin. In T2DM animals we observed a tubule-interstitial injury with significantly increased levels of urinary GGT and ALP, but an absence of tubulointerstitial fibrosis. Kidney proximal tubule cells of T2DM animals showed autophagic vesicles larger than those observed… More >

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