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https://www.readbyqxmd.com/read/28626972/nirca-an-artificial-neural-network-based-insulin-resistance-calculator
#1
Konrad Stawiski, Iwona Pietrzak, Wojciech Młynarski, Wojciech Fendler, Agnieszka Szadkowska
BACKGROUND: Direct measurement of insulin sensitivity in children with type 1 diabetes is cumbersome and time consuming. OBJECTIVE: The aim of our study was to develop novel, accurate machine learning-based methods of insulin resistance estimation in children with type 1 diabetes. METHODS: A hyperinsulinemic hyperglycemic clamp study was performed to evaluate the glucose disposal rate (GDR) in a study group consisting of 315 patients aged 7...
June 19, 2017: Pediatric Diabetes
https://www.readbyqxmd.com/read/28597074/early-metabolic-markers-identify-potential-targets-for-the-prevention-of-type-2-diabetes
#2
Gopal Peddinti, Jeff Cobb, Loic Yengo, Philippe Froguel, Jasmina Kravić, Beverley Balkau, Tiinamaija Tuomi, Tero Aittokallio, Leif Groop
AIMS/HYPOTHESIS: The aims of this study were to evaluate systematically the predictive power of comprehensive metabolomics profiles in predicting the future risk of type 2 diabetes, and to identify a panel of the most predictive metabolic markers. METHODS: We applied an unbiased systems medicine approach to mine metabolite combinations that provide added value in predicting the future incidence of type 2 diabetes beyond known risk factors. We performed mass spectrometry-based targeted, as well as global untargeted, metabolomics, measuring a total of 568 metabolites, in a Finnish cohort of 543 non-diabetic individuals from the Botnia Prospective Study, which included 146 individuals who progressed to type 2 diabetes by the end of a 10 year follow-up period...
June 8, 2017: Diabetologia
https://www.readbyqxmd.com/read/28592309/machine-learning-techniques-for-diabetic-macular-edema-dme-classification-on-sd-oct-images
#3
Khaled Alsaih, Guillaume Lemaitre, Mojdeh Rastgoo, Joan Massich, Désiré Sidibé, Fabrice Meriaudeau
BACKGROUND: Spectral domain optical coherence tomography (OCT) (SD-OCT) is most widely imaging equipment used in ophthalmology to detect diabetic macular edema (DME). Indeed, it offers an accurate visualization of the morphology of the retina as well as the retina layers. METHODS: The dataset used in this study has been acquired by the Singapore Eye Research Institute (SERI), using CIRRUS TM (Carl Zeiss Meditec, Inc., Dublin, CA, USA) SD-OCT device. The dataset consists of 32 OCT volumes (16 DME and 16 normal cases)...
June 7, 2017: Biomedical Engineering Online
https://www.readbyqxmd.com/read/28569238/analyzing-breath-samples-of-hypoglycemic-events-in-type-1-diabetes-patients-towards-developing-an-alternative-to-diabetes-alert-dogs
#4
Amanda P Siegel, Ali Daneshkhah, Dana S Hardin, Sudhir Shrestha, Kody Varahramyan, Mangilal Agarwal
Diabetes is a disease that involves dysregulation of metabolic processes. Patients with type 1 diabetes (T1D) require insulin injections and measured food intake to maintain clinical stability, manually tracking their results by measuring blood glucose levels. Low blood glucose levels, hypoglycemia, can be extremely dangerous and can result in seizures, coma, or even death. Canines trained as diabetes alert dogs (DADs) have demonstrated the ability to detect hypoglycemia from breath, which led us to hypothesize that hypoglycemia, a metabolic dysregulation leading to low blood glucose levels, could be identified through analyzing volatile organic compounds (VOCs) contained within breath...
June 1, 2017: Journal of Breath Research
https://www.readbyqxmd.com/read/28569077/diabetes-and-prediabetes-classification-using-glycemic-variability-indices-from-continuous-glucose-monitoring-data
#5
Giada Acciaroli, Giovanni Sparacino, Liisa Hakaste, Andrea Facchinetti, Giorgio Maria Di Nunzio, Alessandro Palombit, Tiinamaija Tuomi, Rafael Gabriel, Jaime Aranda, Saturio Vega, Claudio Cobelli
BACKGROUND: Tens of glycemic variability (GV) indices are available in the literature to characterize the dynamic properties of glucose concentration profiles from continuous glucose monitoring (CGM) sensors. However, how to exploit the plethora of GV indices for classifying subjects is still controversial. For instance, the basic problem of using GV indices to automatically determine if the subject is healthy rather than affected by impaired glucose tolerance (IGT) or type 2 diabetes (T2D), is still unaddressed...
May 1, 2017: Journal of Diabetes Science and Technology
https://www.readbyqxmd.com/read/28508191/investigations-of-severity-level-measurements-for-diabetic-macular-oedema-using-machine-learning-algorithms
#6
S Murugeswari, R Sukanesh
BACKGROUND: The macula is an important part of the human visual system and is responsible for clear and colour vision. Macular oedema happens when fluid and protein deposit on or below the macula of the eye and cause the macula to thicken and swell. Normally, it occurs due to diabetes called diabetic macular oedema. Diabetic macular oedema (DME) is one of the main causes of visual impairment in patients. AIM: The aims of the present study are to detect and localize abnormalities in blood vessels with respect to macula in order to prevent vision loss for the diabetic patients...
May 15, 2017: Irish Journal of Medical Science
https://www.readbyqxmd.com/read/28503676/learning-optimal-individualized-treatment-rules-from-electronic-health-record-data
#7
Yuanjia Wang, Peng Wu, Ying Liu, Chunhua Weng, Donglin Zeng
Medical research is experiencing a paradigm shift from "one-size-fits-all" strategy to a precision medicine approach where the right therapy, for the right patient, and at the right time, will be prescribed. We propose a statistical method to estimate the optimal individualized treatment rules (ITRs) that are tailored according to subject-specific features using electronic health records (EHR) data. Our approach merges statistical modeling and medical domain knowledge with machine learning algorithms to assist personalized medical decision making using EHR...
October 2016: IEEE International Conference on Healthcare Informatics IEEE International Conference on Healthcare Informatics
https://www.readbyqxmd.com/read/28494618/machine-learning-methods-to-predict-diabetes-complications
#8
Arianna Dagliati, Simone Marini, Lucia Sacchi, Giulia Cogni, Marsida Teliti, Valentina Tibollo, Pasquale De Cata, Luca Chiovato, Riccardo Bellazzi
One of the areas where Artificial Intelligence is having more impact is machine learning, which develops algorithms able to learn patterns and decision rules from data. Machine learning algorithms have been embedded into data mining pipelines, which can combine them with classical statistical strategies, to extract knowledge from data. Within the EU-funded MOSAIC project, a data mining pipeline has been used to derive a set of predictive models of type 2 diabetes mellitus (T2DM) complications based on electronic health record data of nearly one thousand patients...
May 1, 2017: Journal of Diabetes Science and Technology
https://www.readbyqxmd.com/read/28455973/markers-of-arterial-health-could-serve-as-accurate-non-invasive-predictors-of-human-biological-and-chronological-age
#9
Alexander Fedintsev, Daria Kashtanova, Olga Tkacheva, Irina Strazhesko, Anna Kudryavtseva, Ancha Baranova, Alexey Moskalev
The decline in functional capacity is unavoidable consequence of the process of aging. While many anti-aging interventions have been proposed, clinical investigations into anti-aging medicine are limited by lack of reliable techniques for evaluating the rate of ageing. Here we present simple, accurate and cost-efficient techniques for estimation of human biological age, Male and Female Arterial Indices. We started with developing a model which accurately predicts chronological age. Using machine learning, we arrived on a set of four predictors, all of which reflect the functioning of the cardiovascular system...
April 2017: Aging
https://www.readbyqxmd.com/read/28433753/computational-image-analysis-for-prognosis-determination-in-dme
#10
Bianca S Gerendas, Hrvoje Bogunovic, Amir Sadeghipour, Thomas Schlegl, Georg Langs, Sebastian M Waldstein, Ursula Schmidt-Erfurth
In this pilot study, we evaluated the potential of computational image analysis of optical coherence tomography (OCT) data to determine the prognosis of patients with diabetic macular edema (DME). Spectral-domain OCT scans with fully automated retinal layer segmentation and segmentation of intraretinal cystoid fluid (IRC) and subretinal fluid of 629 patients receiving anti-vascular endothelial growth factor therapy for DME in a randomized prospective clinical trial were analyzed. The results were used to define 312 potentially predictive features at three timepoints (baseline, weeks 12 and 24) for best-corrected visual acuity (BCVA) at baseline and after one year used in a random forest prediction path...
April 19, 2017: Vision Research
https://www.readbyqxmd.com/read/28269690/smartsock-a-wearable-platform-for-context-aware-assessment-of-ankle-edema
#11
Ramin Fallahzadeh, Mahdi Pedram, Hassan Ghasemzadeh
Ankle edema an important symptom for monitoring patients with chronic systematic diseases. It is an important indicator of onset or exacerbation of a variety of diseases that disturb cardiovascular, renal, or hepatic system such as heart, liver, and kidney failure, diabetes, etc. The current approaches toward edema assessment are conducted during clinical visits. In-clinic assessments, in addition to being burdensome and expensive, are sometimes not reliable and neglect important contextual factors such as patient's physical activity level and body posture...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28269002/classification-of-large-scale-fundus-image-data-sets-a-cloud-computing-framework
#12
Sohini Roychowdhury
Large medical image data sets with high dimensionality require substantial amount of computation time for data creation and data processing. This paper presents a novel generalized method that finds optimal image-based feature sets that reduce computational time complexity while maximizing overall classification accuracy for detection of diabetic retinopathy (DR). First, region-based and pixel-based features are extracted from fundus images for classification of DR lesions and vessel-like structures. Next, feature ranking strategies are used to distinguish the optimal classification feature sets...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268569/automatic-detection-of-neovascularization-on-optic-disk-region-with-feature-extraction-and-support-vector-machine
#13
Shuang Yu, Di Xiao, Yogesan Kanagasingam
Neovascularization (NV) is a definitive indicator for the onset of Proliferative Diabetic Retinopathy (PDR). The new vessels are fragile and prone to bleed, leading to high risk of sudden vision loss. Automatic detection of NV is an important task in automatic Diabetic Retinopathy (DR) screening as a consequence of the unmet requirement between the growing number of DR patients and limited number of ophthalmologists. This paper focuses on the computer aided detection of neovascularization in the optic disk region...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227951/smartsock-a-wearable-platform-for-context-aware-assessment-of-ankle-edema
#14
Ramin Fallahzadeh, Mahdi Pedram, Hassan Ghasemzadeh, Ramin Fallahzadeh, Mahdi Pedram, Hassan Ghasemzadeh
Ankle edema an important symptom for monitoring patients with chronic systematic diseases. It is an important indicator of onset or exacerbation of a variety of diseases that disturb cardiovascular, renal, or hepatic system such as heart, liver, and kidney failure, diabetes, etc. The current approaches toward edema assessment are conducted during clinical visits. In-clinic assessments, in addition to being burdensome and expensive, are sometimes not reliable and neglect important contextual factors such as patient's physical activity level and body posture...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227212/classification-of-large-scale-fundus-image-data-sets-a-cloud-computing-framework
#15
Sohini Roychowdhury, Sohini Roychowdhury, Sohini Roychowdhury
Large medical image data sets with high dimensionality require substantial amount of computation time for data creation and data processing. This paper presents a novel generalized method that finds optimal image-based feature sets that reduce computational time complexity while maximizing overall classification accuracy for detection of diabetic retinopathy (DR). First, region-based and pixel-based features are extracted from fundus images for classification of DR lesions and vessel-like structures. Next, feature ranking strategies are used to distinguish the optimal classification feature sets...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226747/automatic-detection-of-neovascularization-on-optic-disk-region-with-feature-extraction-and-support-vector-machine
#16
Shuang Yu, Di Xiao, Yogesan Kanagasingam, Shuang Yu, Di Xiao, Yogesan Kanagasingam, Di Xiao, Yogesan Kanagasingam, Shuang Yu
Neovascularization (NV) is a definitive indicator for the onset of Proliferative Diabetic Retinopathy (PDR). The new vessels are fragile and prone to bleed, leading to high risk of sudden vision loss. Automatic detection of NV is an important task in automatic Diabetic Retinopathy (DR) screening as a consequence of the unmet requirement between the growing number of DR patients and limited number of ophthalmologists. This paper focuses on the computer aided detection of neovascularization in the optic disk region...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28155089/predicting-dpp-iv-inhibitors-with-machine-learning-approaches
#17
Jie Cai, Chanjuan Li, Zhihong Liu, Jiewen Du, Jiming Ye, Qiong Gu, Jun Xu
Dipeptidyl peptidase IV (DPP-IV) is a promising Type 2 diabetes mellitus (T2DM) drug target. DPP-IV inhibitors prolong the action of glucagon-like peptide-1 (GLP-1) and gastric inhibitory peptide (GIP), improve glucose homeostasis without weight gain, edema, and hypoglycemia. However, the marketed DPP-IV inhibitors have adverse effects such as nasopharyngitis, headache, nausea, hypersensitivity, skin reactions and pancreatitis. Therefore, it is still expected for novel DPP-IV inhibitors with minimal adverse effects...
April 2017: Journal of Computer-aided Molecular Design
https://www.readbyqxmd.com/read/28138367/machine-learning-and-data-mining-methods-in-diabetes-research
#18
REVIEW
Ioannis Kavakiotis, Olga Tsave, Athanasios Salifoglou, Nicos Maglaveras, Ioannis Vlahavas, Ioanna Chouvarda
The remarkable advances in biotechnology and health sciences have led to a significant production of data, such as high throughput genetic data and clinical information, generated from large Electronic Health Records (EHRs). To this end, application of machine learning and data mining methods in biosciences is presently, more than ever before, vital and indispensable in efforts to transform intelligently all available information into valuable knowledge. Diabetes mellitus (DM) is defined as a group of metabolic disorders exerting significant pressure on human health worldwide...
2017: Computational and Structural Biotechnology Journal
https://www.readbyqxmd.com/read/28137222/machine-learning-and-molecular-dynamics-based-insights-into-mode-of-actions-of-insulin-degrading-enzyme-modulators
#19
Salma Jamal, Sukriti Goyal, Asheesh Shanker, Abhinav Grover
BACKGROUND: Alzheimer's disease (AD) is one of the most common lethal neurodegenerative disorders having impact on the lives of millions of people worldwide. The disease lacks effective treatment options and the unavailability of the drugs to cure the disease necessitates the development of effectual anti-Alzheimer drugs. Several mechanisms have been reported underlying the association of the two disorders, diabetes and dementia, one among which is the insulin-degrading enzyme (IDE) which is known to degrade insulin as well beta-amyloid peptides...
January 30, 2017: Combinatorial Chemistry & High Throughput Screening
https://www.readbyqxmd.com/read/28113284/type-2-diabetes-screening-test-by-means-of-a-pulse-oximeter
#20
Enrique Moreno, Maria Jose Lujan, Maria Anyo Lujan, Montse Torrres Rusinol, Paqui Juarez Fernandez, Pilar Nunez Manrique, Cristina Aragon Trivino, Magda Miquel, Marife Rodriguez, M Jose Gonzalez Burguillos
In this paper, we propose a method for screening for the presence of type 2 diabetes by means of the signal obtained from a pulse oximeter. The screening system consists of two parts; the first analyses the signal obtained from the pulse oximeter, and the second consists of a machine-learning module. The system consists of a front end that extracts a set of features form the pulse oximeter signal. These features are based on physiological considerations. The set of features were the input of a machine-learning algorithm that determined the class of the input sample, i...
April 20, 2016: IEEE Transactions on Bio-medical Engineering
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