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https://www.readbyqxmd.com/read/27902695/text-mining-genotype-phenotype-relationships-from-biomedical-literature-for-database-curation-and-precision-medicine
#1
Ayush Singhal, Michael Simmons, Zhiyong Lu
The practice of precision medicine will ultimately require databases of genes and mutations for healthcare providers to reference in order to understand the clinical implications of each patient's genetic makeup. Although the highest quality databases require manual curation, text mining tools can facilitate the curation process, increasing accuracy, coverage, and productivity. However, to date there are no available text mining tools that offer high-accuracy performance for extracting such triplets from biomedical literature...
November 2016: PLoS Computational Biology
https://www.readbyqxmd.com/read/27898976/development-and-validation-of-a-deep-learning-algorithm-for-detection-of-diabetic-retinopathy-in-retinal-fundus-photographs
#2
Varun Gulshan, Lily Peng, Marc Coram, Martin C Stumpe, Derek Wu, Arunachalam Narayanaswamy, Subhashini Venugopalan, Kasumi Widner, Tom Madams, Jorge Cuadros, Ramasamy Kim, Rajiv Raman, Philip C Nelson, Jessica L Mega, Dale R Webster
Importance: Deep learning is a family of computational methods that allow an algorithm to program itself by learning from a large set of examples that demonstrate the desired behavior, removing the need to specify rules explicitly. Application of these methods to medical imaging requires further assessment and validation. Objective: To apply deep learning to create an algorithm for automated detection of diabetic retinopathy and diabetic macular edema in retinal fundus photographs...
November 29, 2016: JAMA: the Journal of the American Medical Association
https://www.readbyqxmd.com/read/27893380/area-determination-of-diabetic-foot-ulcer-images-using-a-cascaded-two-stage-svm-based-classification
#3
Lei Wang, Peder Pedersen, Emmanuel Agu, Diane Strong, Bengisu Tulu
It is standard practice for clinicians and nurses to primarily assess patients' wounds via visual examination. This subjective method can be inaccurate in wound assessment and also represents a significant clinical workload. Hence, computer-based systems, especially implemented on mobile devices, can provide automatic, quantitative wound assessment and can thus be valuable for accurately monitoring wound healing status. Out of all wound assessment parameters, the measurement of the wound area is the most suitable for automated analysis...
November 23, 2016: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/27866845/untargeted-serum-metabolomics-reveals-fu-zhu-jiang-tang-tablet-and-its-optimal-combination-improve-an-impaired-glucose-and-lipid-metabolism-in-type-ii-diabetic-rats
#4
Yi Tao, Xi Chen, Hao Cai, Weidong Li, Baochang Cai, Chuan Chai, Liuqing Di, Liyun Shi, Lihong Hu
Fu-Zhu-Jiang-Tang tablet, a six-herb preparation, was proved to show beneficial effects on type II diabetes patients in clinical. This study aims to optimize the component proportion of the six-herb preparation and explore the serum metabolic signatures of type II diabetes rats after treatment with Fu-Zhu-Jiang-Tang tablet and its optimal combination. The component proportion of the preparation was optimized using uniform experimental design and machine learning techniques. Untargeted GC-MS metabolomic experiments were carried out with serum samples from model group and treatment groups...
November 13, 2016: Journal of Chromatography. B, Analytical Technologies in the Biomedical and Life Sciences
https://www.readbyqxmd.com/read/27848884/understanding-the-structural-basis-for-inhibition-of-cyclin-dependent-kinases-new-pieces-in-the-molecular-puzzle
#5
Nayara M Bernhardt Levin, Val Oliveira Pintro, Maurício Boff de Ávila, Bruna Boldrini de Mattos, Walter F De Azevedo
BACKGROUND: Cyclin-dependent kinases (CDKs) comprise an important protein family for development of drugs, mostly aimed for use in treatment of cancer but there is also potential for development of drugs for neurodegenerative diseases and diabetes. Since the early 1990s, structural studies have been carried out on CDKs, in order to determine the structural basis for inhibition of this protein target. OBJECTIVE: Our goal here is to review recent structural studies focused on CDKs...
November 16, 2016: Current Drug Targets
https://www.readbyqxmd.com/read/27830057/automated-analysis-of-retinal-imaging-using-machine-learning%C3%A2-techniques-for-computer-vision
#6
Jeffrey De Fauw, Pearse Keane, Nenad Tomasev, Daniel Visentin, George van den Driessche, Mike Johnson, Cian O Hughes, Carlton Chu, Joseph Ledsam, Trevor Back, Tunde Peto, Geraint Rees, Hugh Montgomery, Rosalind Raine, Olaf Ronneberger, Julien Cornebise
There are almost two million people in the United Kingdom living with sight loss, including around 360,000 people who are registered as blind or partially sighted. Sight threatening diseases, such as diabetic retinopathy and age related macular degeneration have contributed to the 40% increase in outpatient attendances in the last decade but are amenable to early detection and monitoring. With early and appropriate intervention, blindness may be prevented in many cases. Ophthalmic imaging provides a way to diagnose and objectively assess the progression of a number of pathologies including neovascular ("wet") age-related macular degeneration (wet AMD) and diabetic retinopathy...
2016: F1000Research
https://www.readbyqxmd.com/read/27787616/evaluation-of-methods-to-estimate-missing-days-supply-within-pharmacy-data-of-the-clinical-practice-research-datalink-cprd-and-the-health-improvement-network-thin
#7
Kirsten J Lum, Craig W Newcomb, Jason A Roy, Dena M Carbonari, M Elle Saine, Serena Cardillo, Harshvinder Bhullar, Arlene M Gallagher, Vincent Lo Re
PURPOSE: The extent to which days' supply data are missing in pharmacoepidemiologic databases and effective methods for estimation is unknown. We determined the percentage of missing days' supply on prescription and patient levels for oral anti-diabetic drugs (OADs) and evaluated three methods for estimating days' supply within the Clinical Practice Research Datalink (CPRD) and The Health Improvement Network (THIN). METHODS: We estimated the percentage of OAD prescriptions and patients with missing days' supply in each database from 2009 to 2013...
October 27, 2016: European Journal of Clinical Pharmacology
https://www.readbyqxmd.com/read/27782018/assessment-of-computer-assisted-screening-technology-for-diabetic-retinopathy-screening-in-india-preliminary-results-and-recommendations-from-a-pilot-study
#8
Sheila John, Keerthi Ram, Mohanasankar Sivaprakasam, Rajiv Raman
BACKGROUND: Diabetic retinopathy (DR) is regarded as a major cause of preventable blindness, which can be detected and treated if the cases are identified by screening. Screening for DR is therefore being practiced in developed countries, and tele screening has been a prominent model of delivery of eye care for screening DR. AIM: Our study has been designed to provide inputs on the suitability of a computer-assisted DR screening solution, for use in a larger prospective study...
2016: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/27753745/identifying-specific-combinations-of-multimorbidity-that-contribute-to-health-care-resource-utilization-an-analytic-approach
#9
Nicholas K Schiltz, David F Warner, Jiayang Sun, Paul M Bakaki, Avi Dor, Charles W Given, Kurt C Stange, Siran M Koroukian
BACKGROUND: Multimorbidity affects the majority of elderly adults and is associated with higher health costs and utilization, but how specific patterns of morbidity influence resource use is less understood. OBJECTIVE: The objective was to identify specific combinations of chronic conditions, functional limitations, and geriatric syndromes associated with direct medical costs and inpatient utilization. DESIGN: Retrospective cohort study using the Health and Retirement Study (2008-2010) linked to Medicare claims...
October 6, 2016: Medical Care
https://www.readbyqxmd.com/read/27752272/predicting-metabolic-syndrome-using-decision-tree-and-support-vector-machine-methods
#10
Farzaneh Karimi-Alavijeh, Saeed Jalili, Masoumeh Sadeghi
BACKGROUND: Metabolic syndrome which underlies the increased prevalence of cardiovascular disease and Type 2 diabetes is considered as a group of metabolic abnormalities including central obesity, hypertriglyceridemia, glucose intolerance, hypertension, and dyslipidemia. Recently, artificial intelligence based health-care systems are highly regarded because of its success in diagnosis, prediction, and choice of treatment. This study employs machine learning technics for predict the metabolic syndrome...
May 2016: ARYA Atherosclerosis
https://www.readbyqxmd.com/read/27751984/building-a-national-neighborhood-dataset-from-geotagged-twitter-data-for-indicators-of-happiness-diet-and-physical-activity
#11
Quynh C Nguyen, Dapeng Li, Hsien-Wen Meng, Suraj Kath, Elaine Nsoesie, Feifei Li, Ming Wen
BACKGROUND: Studies suggest that where people live, play, and work can influence health and well-being. However, the dearth of neighborhood data, especially data that is timely and consistent across geographies, hinders understanding of the effects of neighborhoods on health. Social media data represents a possible new data resource for neighborhood research. OBJECTIVE: The aim of this study was to build, from geotagged Twitter data, a national neighborhood database with area-level indicators of well-being and health behaviors...
October 17, 2016: JMIR Public Health and Surveillance
https://www.readbyqxmd.com/read/27749844/prospective-functional-classification-of-all-possible-missense-variants-in-pparg
#12
Amit R Majithia, Ben Tsuda, Maura Agostini, Keerthana Gnanapradeepan, Robert Rice, Gina Peloso, Kashyap A Patel, Xiaolan Zhang, Marjoleine F Broekema, Nick Patterson, Marc Duby, Ted Sharpe, Eric Kalkhoven, Evan D Rosen, Inês Barroso, Sian Ellard, Sekar Kathiresan, Stephen O'Rahilly, Krishna Chatterjee, Jose C Florez, Tarjei Mikkelsen, David B Savage, David Altshuler
Clinical exome sequencing routinely identifies missense variants in disease-related genes, but functional characterization is rarely undertaken, leading to diagnostic uncertainty. For example, mutations in PPARG cause Mendelian lipodystrophy and increase risk of type 2 diabetes (T2D). Although approximately 1 in 500 people harbor missense variants in PPARG, most are of unknown consequence. To prospectively characterize PPARγ variants, we used highly parallel oligonucleotide synthesis to construct a library encoding all 9,595 possible single-amino acid substitutions...
October 17, 2016: Nature Genetics
https://www.readbyqxmd.com/read/27727289/prediction-of-incident-diabetes-in-the-jackson-heart-study-using-high-dimensional-machine-learning
#13
Ramon Casanova, Santiago Saldana, Sean L Simpson, Mary E Lacy, Angela R Subauste, Chad Blackshear, Lynne Wagenknecht, Alain G Bertoni
Statistical models to predict incident diabetes are often based on limited variables. Here we pursued two main goals: 1) investigate the relative performance of a machine learning method such as Random Forests (RF) for detecting incident diabetes in a high-dimensional setting defined by a large set of observational data, and 2) uncover potential predictors of diabetes. The Jackson Heart Study collected data at baseline and in two follow-up visits from 5,301 African Americans. We excluded those with baseline diabetes and no follow-up, leaving 3,633 individuals for analyses...
2016: PloS One
https://www.readbyqxmd.com/read/27722975/activity-recognition-for-diabetic-patients-using-a-smartphone
#14
Božidara Cvetković, Vito Janko, Alfonso E Romero, Özgür Kafalı, Kostas Stathis, Mitja Luštrek
Diabetes is a disease that has to be managed through appropriate lifestyle. Technology can help with this, particularly when it is designed so that it does not impose an additional burden on the patient. This paper presents an approach that combines machine-learning and symbolic reasoning to recognise high-level lifestyle activities using sensor data obtained primarily from the patient's smartphone. We compare five methods for machine-learning which differ in the amount of manually labelled data by the user, to investigate the trade-off between the labelling effort and recognition accuracy...
December 2016: Journal of Medical Systems
https://www.readbyqxmd.com/read/27660645/an-active-learning-classifier-for-further-reducing-diabetic-retinopathy-screening-system-cost
#15
Yinan Zhang, Mingqiang An
Diabetic retinopathy (DR) screening system raises a financial problem. For further reducing DR screening cost, an active learning classifier is proposed in this paper. Our approach identifies retinal images based on features extracted by anatomical part recognition and lesion detection algorithms. Kernel extreme learning machine (KELM) is a rapid classifier for solving classification problems in high dimensional space. Both active learning and ensemble technique elevate performance of KELM when using small training dataset...
2016: Computational and Mathematical Methods in Medicine
https://www.readbyqxmd.com/read/27642290/machine-learning-to-predict-rapid-progression-of-carotid-atherosclerosis-in-patients-with-impaired-glucose-tolerance
#16
Xia Hu, Peter D Reaven, Aramesh Saremi, Ninghao Liu, Mohammad Ali Abbasi, Huan Liu, Raymond Q Migrino
OBJECTIVES: Prediabetes is a major epidemic and is associated with adverse cardio-cerebrovascular outcomes. Early identification of patients who will develop rapid progression of atherosclerosis could be beneficial for improved risk stratification. In this paper, we investigate important factors impacting the prediction, using several machine learning methods, of rapid progression of carotid intima-media thickness in impaired glucose tolerance (IGT) participants. METHODS: In the Actos Now for Prevention of Diabetes (ACT NOW) study, 382 participants with IGT underwent carotid intima-media thickness (CIMT) ultrasound evaluation at baseline and at 15-18 months, and were divided into rapid progressors (RP, n = 39, 58 ± 17...
December 2016: EURASIP Journal on Bioinformatics & Systems Biology
https://www.readbyqxmd.com/read/27577499/towards-a-personal-health-record-system-for-the-assesment-and-monitoring-of-sedentary-behavior-in-indoor-locations
#17
Jesus D Ceron, Diego M Lopez
BACKGROUND: Sedentary behavior has been associated to the development of noncommunicable diseases (NCD) such as cardiovascular diseases (CVD), type 2 diabetes, and cancer. Accelerometers and inclinometers have been used to estimate sedentary behaviors, however a major limitation is that these devices do not provide contextual information such as the activity performed, e.g., TV viewing, sitting at work, driving, etc. OBJECTIVE: The main objective of the thesis is to propose and evaluate a Personal Health Record System to support the assessment and monitoring of sedentary behaviors...
2016: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/27566751/screening-diabetes-mellitus-2-based-on-electronic-health-records-using-temporal-features
#18
Angela Pimentel, André V Carreiro, Rogério T Ribeiro, Hugo Gamboa
The prevalence of type 2 diabetes mellitus is increasing worldwide. Current methods of treating diabetes remain inadequate, and therefore, prevention with screening methods is the most appropriate process to reduce the burden of diabetes and its complications. We propose a new prognostic approach for type 2 diabetes mellitus based on electronic health records without using the current invasive techniques that are related to the disease (e.g. glucose level or glycated hemoglobin (HbA1c)). Our methodology is based on machine learning frameworks with data enrichment using temporal features...
August 26, 2016: Health Informatics Journal
https://www.readbyqxmd.com/read/27560544/a-supervised-learning-framework-for-pancreatic-islet-segmentation-with-multi-scale-color-texture-features-and-rolling-guidance-filters
#19
Yue Huang, Chi Liu, John F Eisses, Sohail Z Husain, Gustavo K Rohde
Islet cell quantification and function is important for developing novel therapeutic interventions for diabetes. Existing methods of pancreatic islet segmentation in histopathological images depend strongly on cell/nuclei detection, and thus are limited due to a wide variance in the appearance of pancreatic islets. In this paper, we propose a supervised learning pipeline to segment pancreatic islets in histopathological images, which does not require cell detection. The proposed framework firstly partitions images into superpixels, and then extracts multi-scale color-texture features from each superpixel and processes these features using rolling guidance filters, in order to simultaneously reduce inter-class ambiguity and intra-class variation...
October 2016: Cytometry. Part A: the Journal of the International Society for Analytical Cytology
https://www.readbyqxmd.com/read/27541627/identifying-and-investigating-unexpected-response-to-treatment-a-diabetes-case-study
#20
Michal Ozery-Flato, Liat Ein-Dor, Naama Parush-Shear-Yashuv, Ranit Aharonov, Hani Neuvirth, Martin S Kohn, Jianying Hu
The availability of electronic health records creates fertile ground for developing computational models of various medical conditions. We present a new approach for detecting and analyzing patients with unexpected responses to treatment, building on machine learning and statistical methodology. Given a specific patient, we compute a statistical score for the deviation of the patient's response from responses observed in other patients having similar characteristics and medication regimens. These scores are used to define cohorts of patients showing deviant responses...
September 2016: Big Data
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