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https://www.readbyqxmd.com/read/28092510/unobtrusive-and-wearable-systems-for-automatic-dietary-monitoring
#1
Temiloluwa Prioleau, Elliot Moore, Maysam Ghovanloo
The threat of obesity, diabetes, anorexia and bulimia in our society today has motivated extensive research on dietary monitoring. Standard self-report methods such as 24-hour recall and food frequency questionnaires are expensive, burdensome and unrealiable to handle the growing health crisis. Long-term activity monitoring in daily living is a promising approach to provide individuals with quantitative feedback that can encourage healthier habits. Although several studies have attempted automating dietary monitoring using wearable, hand-held, smartobject, and environmental systems, it remains an open research problem...
January 16, 2017: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/28068461/a-new-prediction-model-for-evaluating-treatment-resistant-depression
#2
Alexander Kautzky, Pia Baldinger-Melich, Georg S Kranz, Thomas Vanicek, Daniel Souery, Stuart Montgomery, Julien Mendlewicz, Joseph Zohar, Alessandro Serretti, Rupert Lanzenberger, Siegfried Kasper
OBJECTIVE: Despite a broad arsenal of antidepressants, about a third of patients suffering from major depressive disorder (MDD) do not respond sufficiently to adequate treatment. Using the data pool of the Group for the Study of Resistant Depression and machine learning, we intended to draw new insights featuring 48 clinical, sociodemographic, and psychosocial predictors for treatment outcome. METHOD: Patients were enrolled starting from January 2000 and diagnosed according to DSM-IV...
January 3, 2017: Journal of Clinical Psychiatry
https://www.readbyqxmd.com/read/28060227/preoperative-opioid-use-is-associated-with-early-revision-after-total-knee-arthroplasty-a-study-of-male-patients-treated-in-the-veterans-affairs-system
#3
Alon Ben-Ari, Howard Chansky, Irene Rozet
BACKGROUND: Opioid use is endemic in the U.S. and is associated with morbidity and mortality. The impact of long-term opioid use on joint-replacement outcomes remains unknown. We tested the hypothesis that use of opioids is associated with adverse outcomes after total knee arthroplasty (TKA). METHODS: We performed a retrospective analysis of patients who had had TKA within the U.S. Veterans Affairs (VA) system over a 6-year period and had been followed for 1 year postoperatively...
January 4, 2017: Journal of Bone and Joint Surgery. American Volume
https://www.readbyqxmd.com/read/28034409/visualizing-the-knowledge-structure-and-evolution-of-big-data-research-in-healthcare-informatics
#4
REVIEW
Dongxiao Gu, Jingjing Li, Xingguo Li, Changyong Liang
BACKGROUND: In recent years, the literature associated with healthcare big data has grown rapidly, but few studies have used bibliometrics and a visualization approach to conduct deep mining and reveal a panorama of the healthcare big data field. METHODS: To explore the foundational knowledge and research hotspots of big data research in the field of healthcare informatics, this study conducted a series of bibliometric analyses on the related literature, including papers' production trends in the field and the trend of each paper's co-author number, the distribution of core institutions and countries, the core literature distribution, the related information of prolific authors and innovation paths in the field, a keyword co-occurrence analysis, and research hotspots and trends for the future...
February 2017: International Journal of Medical Informatics
https://www.readbyqxmd.com/read/28018716/machine-learning-based-detection-of-age-related-macular-degeneration-amd-and-diabetic-macular-edema-dme-from-optical-coherence-tomography-oct-images
#5
Yu Wang, Yaonan Zhang, Zhaomin Yao, Ruixue Zhao, Fengfeng Zhou
Non-lethal macular diseases greatly impact patients' life quality, and will cause vision loss at the late stages. Visual inspection of the optical coherence tomography (OCT) images by the experienced clinicians is the main diagnosis technique. We proposed a computer-aided diagnosis (CAD) model to discriminate age-related macular degeneration (AMD), diabetic macular edema (DME) and healthy macula. The linear configuration pattern (LCP) based features of the OCT images were screened by the Correlation-based Feature Subset (CFS) selection algorithm...
December 1, 2016: Biomedical Optics Express
https://www.readbyqxmd.com/read/28006676/multiple-machine-learning-based-descriptive-and-predictive-workflow-for-the-identification-of-potential-ptp1b-inhibitors
#6
Sharat Chandra, Jyotsana Pandey, Akhilesh Kumar Tamrakar, Mohammad Imran Siddiqi
In insulin and leptin signaling pathway, Protein-Tyrosine Phosphatase 1B (PTP1B) plays a crucial controlling role as a negative regulator, which makes it an attractive therapeutic target for both Type-2 Diabetes (T2D) and obesity. In this work, we have generated classification models by using the inhibition data set of known PTP1B inhibitors to identify new inhibitors of PTP1B utilizing multiple machine learning techniques like naïve Bayesian, random forest, support vector machine and k-nearest neighbors, along with structural fingerprints and selected molecular descriptors...
January 2017: Journal of Molecular Graphics & Modelling
https://www.readbyqxmd.com/read/27982668/data-driven-clinical-and-cost-pathways-for-chronic-care-delivery
#7
Yiye Zhang, Rema Padman
OBJECTIVES: This study illustrates a systematic methodology to embed medical costs into the exact flow of clinical events associated with chronic care delivery. We summarized and visualized the results using clinical and cost data, with the goal of empowering patients and care providers with actionable information as they navigate through a multitude of clinical events and medical expenses. STUDY DESIGN: We analyzed the electronic health records (EHRs) and medication cost data of 288 patients from 2009 to 2011, whose initial diagnoses included chronic kidney disease stage 3, hypertension, and diabetes...
December 2016: American Journal of Managed Care
https://www.readbyqxmd.com/read/27935995/into-the-bowels-of-depression-unravelling-medical-symptoms-associated-with-depression-by-applying-machine-learning-techniques-to-a-community-based-population-sample
#8
Joanna F Dipnall, Julie A Pasco, Michael Berk, Lana J Williams, Seetal Dodd, Felice N Jacka, Denny Meyer
BACKGROUND: Depression is commonly comorbid with many other somatic diseases and symptoms. Identification of individuals in clusters with comorbid symptoms may reveal new pathophysiological mechanisms and treatment targets. The aim of this research was to combine machine-learning (ML) algorithms with traditional regression techniques by utilising self-reported medical symptoms to identify and describe clusters of individuals with increased rates of depression from a large cross-sectional community based population epidemiological study...
2016: PloS One
https://www.readbyqxmd.com/read/27932531/development-of-type-2-diabetes-mellitus-phenotyping-framework-using-expert-knowledge-and-machine-learning-approach
#9
Rina Kagawa, Yoshimasa Kawazoe, Yusuke Ida, Emiko Shinohara, Katsuya Tanaka, Takeshi Imai, Kazuhiko Ohe
BACKGROUND: Phenotyping is an automated technique that can be used to distinguish patients based on electronic health records. To improve the quality of medical care and advance type 2 diabetes mellitus (T2DM) research, the demand for T2DM phenotyping has been increasing. Some existing phenotyping algorithms are not sufficiently accurate for screening or identifying clinical research subjects. OBJECTIVE: We propose a practical phenotyping framework using both expert knowledge and a machine learning approach to develop 2 phenotyping algorithms: one is for screening; the other is for identifying research subjects...
December 7, 2016: Journal of Diabetes Science and Technology
https://www.readbyqxmd.com/read/27919371/a-machine-learning-based-framework-to-identify-type-2-diabetes-through-electronic-health-records
#10
Tao Zheng, Wei Xie, Liling Xu, Xiaoying He, Ya Zhang, Mingrong You, Gong Yang, You Chen
OBJECTIVE: To discover diverse genotype-phenotype associations affiliated with Type 2 Diabetes Mellitus (T2DM) via genome-wide association study (GWAS) and phenome-wide association study (PheWAS), more cases (T2DM subjects) and controls (subjects without T2DM) are required to be identified (e.g., via Electronic Health Records (EHR)). However, existing expert based identification algorithms often suffer in a low recall rate and could miss a large number of valuable samples under conservative filtering standards...
January 2017: International Journal of Medical Informatics
https://www.readbyqxmd.com/read/27902695/text-mining-genotype-phenotype-relationships-from-biomedical-literature-for-database-curation-and-precision-medicine
#11
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
#12
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...
13, 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
#13
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
#14
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...
January 1, 2017: 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
#15
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
#16
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
#17
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...
January 2017: 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
#18
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
#19
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
#20
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
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