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https://www.readbyqxmd.com/read/28531966/how-do-disturbances-and-climate-effects-on-carbon-and-water-fluxes-differ-between-multi-aged-and-even-aged-coniferous-forests
#1
Xuguang Tang, Hengpeng Li, Mingguo Ma, Li Yao, Matthias Peichl, Altaf Arain, Xibao Xu, Michael Goulden
Disturbances and climatic changes significantly affect forest ecosystem productivity, water use efficiency (WUE) and carbon (C) flux dynamics. A deep understanding of terrestrial feedbacks to such effects and recovery mechanisms in forests across contrasting climatic regimes is essential to predict future regional/global C and water budgets, which are also closely related to the potential forest management decisions. However, the resilience of multi-aged and even-aged forests to disturbances has been debated for >60years because of technical measurement constraints...
May 18, 2017: Science of the Total Environment
https://www.readbyqxmd.com/read/28531775/a-protocol-for-sustained-reduction-of-total-parenteral-nutrition-and-cost-savings-by-improvement-of-nutritional-care-in-hospitals
#2
Rian van Schaik, Kurt Van den Abeele, Glenn Melsens, Peter Schepens, Truus Lanssens, Bernadette Vlaemynck, Maria Devisch, Theo A Niewold
BACKGROUND AND AIMS: Malnutrition and the use of Total Parenteral Nutrition (TPN) contribute considerably to hospital costs. Recently, we reported on the introduction of malnutrition screening and monitoring of TPN use in our hospital, which resulted in a large (40%) reduction in TPN and improved quality of nutritional care in two years (2011/12). Here, we aimed to assure continuation of improved care by developing a detailed malnutrition screening and TPN use protocol involving instruction tools for hospital staff, while monitoring the results in the following two years (2013/14)...
October 2016: Clinical Nutrition ESPEN
https://www.readbyqxmd.com/read/28526584/a-simple-algorithm-to-predict-falls-in-primary-care-patients-aged-65-to-74%C3%A2-years-the-international-mobility-in-aging-study
#3
Fernando Gomez, Yan Yan Wu, Mohammad Auais, Afshin Vafaei, Maria-Victoria Zunzunegui
OBJECTIVE: Primary care practitioners need simple algorithms to identify older adults at higher risks of falling. Classification and regression tree (CaRT) analyses are useful tools for identification of clinical predictors of falls. DESIGN: Prospective cohort. SETTING: Community-dwelling older adults at 5 diverse sites: Tirana (Albania), Natal (Brazil), Manizales (Colombia), Kingston (Ontario, Canada), and Saint-Hyacinthe (Quebec, Canada)...
May 16, 2017: Journal of the American Medical Directors Association
https://www.readbyqxmd.com/read/28526460/semi-supervised-medical-entity-recognition-a-study-on-spanish-and-swedish-clinical-corpora
#4
Alicia Pérez, Rebecka Weegar, Arantza Casillas, Koldo Gojenola, Maite Oronoz, Hercules Dalianis
OBJECTIVE: The goal of this study is to investigate entity recognition within Electronic Health Records (EHRs) focusing on Spanish and Swedish. Of particular importance is a robust representation of the entities. In our case, we utilized unsupervised methods to generate such representations. METHODS: The significance of this work stands on its experimental layout. The experiments were carried out under the same conditions for both languages. Several classification approaches were explored: maximum probability, CRF, Perceptron and SVM...
May 16, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28525350/comparing-four-methods-for-estimating-tree-based-treatment-regimes
#5
Aniek Sies, Iven Van Mechelen
When multiple treatment alternatives are available for a certain psychological or medical problem, an important challenge is to find an optimal treatment regime, which specifies for each patient the most effective treatment alternative given his or her pattern of pretreatment characteristics. The focus of this paper is on tree-based treatment regimes, which link an optimal treatment alternative to each leaf of a tree; as such they provide an insightful representation of the decision structure underlying the regime...
May 12, 2017: International Journal of Biostatistics
https://www.readbyqxmd.com/read/28523981/classification-of-lunge-biomechanics-with-multiple-and-individual-inertial-measurement-units
#6
Martin A O'Reilly, Darragh F Whelan, Tomas E Ward, Eamonn Delahunt, Brian Caulfield
Lunges are a common, compound lower limb resistance exercise. If completed with aberrant technique, the increased stress on the joints used may increase risk of injury. This study sought to first investigate the ability of inertial measurement units (IMUs), when used in isolation and combination, to (a) classify acceptable and aberrant lunge technique (b) classify exact deviations in lunge technique. We then sought to investigate the most important features and establish the minimum number of top-ranked features and decision trees that are needed to maintain maximal system classification efficacy...
May 19, 2017: Sports Biomechanics
https://www.readbyqxmd.com/read/28513802/prevalence-and-factors-associated-with-self-reported-disability-a-comparison-between-genders
#7
Mônica Faria Felicíssimo, Amélia Augusta de Lima Friche, Amanda Cristina de Souza Andrade, Roseli Gomes de Andrade, Dário Alves da Silva Costa, César Coelho Xavier, Fernando Augusto Proietti, Waleska Teixeira Caiaffa
Objective: To estimate the prevalence of disability and its association with sociodemographic and health characteristics stratified by sex. Methods: This is a cross-sectional study with a probabilistic sample including 4,048 residents aged ≥ 18 years in two health districts of Belo Horizonte (MG), Brazil, during the period from 2008 to 2009. The outcome variable "disability" was established based on self-reported problems in body functions or structures. Sociodemographic characteristics ("sex," "age," "skin color," "marital status," "years of schooling," and "family income") and health ("reported morbidity," "health self-assessment," "quality of life," and "life satisfaction") were the explanatory variables...
January 2017: Revista Brasileira de Epidemiologia, Brazilian Journal of Epidemiology
https://www.readbyqxmd.com/read/28511315/-a-cost-benefit-analysis-of-occupational-disease-reporting-in-china
#8
X Z Tang, Q Zeng, D S Liu
Objective: To perform a cost-benefit analysis of the occupational disease reporting system in China, and to provide a basis for effective resource allocation. Methods: The data on the cost of occupational diseases were collected from China Health Statistics Yearbook 2013, the estimated benefit data were collected from published articles in China and foreign countries, and the probability data were collected from the occupational diseasereports published by health and family planning administrative departments...
March 20, 2017: Chinese Journal of Industrial Hygiene and Occupational Diseases
https://www.readbyqxmd.com/read/28508814/plausibility-of-individual-decisions-from-random-forests-in-clinical-predictive-modelling-applications
#9
Dieter Hayn, Harald Walch, Jörg Stieg, Karl Kreiner, Hubert Ebner, Günter Schreier
BACKGROUND: Machine learning algorithms are a promising approach to help physicians to deal with the ever increasing amount of data collected in healthcare each day. However, interpretation of suggestions derived from predictive models can be difficult. OBJECTIVES: The aim of this work was to quantify the influence of a specific feature on an individual decision proposed by a random forest (RF). METHODS: For each decision tree within the RF, the influence of each feature on a specific decision (FID) was quantified...
2017: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/28508544/a-decision-tree-for-nonmetric-sex-assessment-from-the-skull
#10
Natalie R Langley, Beatrix Dudzik, Alesia Cloutier
This study uses five well-documented cranial nonmetric traits (glabella, mastoid process, mental eminence, supraorbital margin, and nuchal crest) and one additional trait (zygomatic extension) to develop a validated decision tree for sex assessment. The decision tree was built and cross-validated on a sample of 293 U.S. White individuals from the William M. Bass Donated Skeletal Collection. Ordinal scores from the six traits were analyzed using the partition modeling option in JMP Pro 12. A holdout sample of 50 skulls was used to test the model...
May 16, 2017: Journal of Forensic Sciences
https://www.readbyqxmd.com/read/28508375/an-integration-of-decision-tree-and-visual-analysis-to-analyze-intracranial-pressure
#11
Soo-Yeon Ji, Kayvan Najarian, Toan Huynh, Dong Hyun Jeong
In Traumatic Brain Injury (TBI), elevated Intracranial Pressure (ICP) causes severe brain damages due to hemorrhage and swelling. Monitoring ICP plays an important role in the treatment of TBI patients because ICP is considered a strong predictor of neurological outcome and a potentially amenable method to treat patients. However, it is difficult to predict and measure accurate ICP due to the complex nature of patients' clinical conditions. ICP monitoring for severe TBI patient is a challenging problem for clinicians because traditionally known ICP monitoring is an invasive procedure by placing a device inside the brain to measure pressure...
2017: Methods in Molecular Biology
https://www.readbyqxmd.com/read/28508298/stability-of-control-networks-in-autonomous-homeostatic-regulation-of-stem-cell-lineages
#12
Natalia L Komarova, P van den Driessche
Design principles of biological networks have been studied extensively in the context of protein-protein interaction networks, metabolic networks, and regulatory (transcriptional) networks. Here we consider regulation networks that occur on larger scales, namely the cell-to-cell signaling networks that connect groups of cells in multicellular organisms. These are the feedback loops that orchestrate the complex dynamics of cell fate decisions and are necessary for the maintenance of homeostasis in stem cell lineages...
May 15, 2017: Bulletin of Mathematical Biology
https://www.readbyqxmd.com/read/28505027/automated-surveillance-of-healthcare-associated-infections-state-of-the-art
#13
Meander E Sips, Marc J M Bonten, Maaike S M van Mourik
PURPOSE OF REVIEW: This review describes recent advances in the field of automated surveillance of healthcare-associated infections (HAIs), with a focus on data sources and the development of semiautomated or fully automated algorithms. RECENT FINDINGS: The availability of high-quality data in electronic health records and a well-designed information technology (IT) infrastructure to access these data are indispensable for successful implementation of automated HAI surveillance...
May 12, 2017: Current Opinion in Infectious Diseases
https://www.readbyqxmd.com/read/28503676/learning-optimal-individualized-treatment-rules-from-electronic-health-record-data
#14
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/28500013/new-splitting-criteria-for-decision-trees-in-stationary-data-streams
#15
Maciej Jaworski, Piotr Duda, Leszek Rutkowski
The most popular tools for stream data mining are based on decision trees. In previous 15 years, all designed methods, headed by the very fast decision tree algorithm, relayed on Hoeffding's inequality and hundreds of researchers followed this scheme. Recently, we have demonstrated that although the Hoeffding decision trees are an effective tool for dealing with stream data, they are a purely heuristic procedure; for example, classical decision trees such as ID3 or CART cannot be adopted to data stream mining using Hoeffding's inequality...
May 10, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28496143/serum-metabolomic-profiles-for-breast-cancer-diagnosis-grading-and-staging-by-gas-chromatography-mass-spectrometry
#16
Naila Irum Hadi, Qamar Jamal, Ayesha Iqbal, Fouzia Shaikh, Saleem Somroo, Syed Ghulam Musharraf
Detection of metabolic signature for breast cancer (BC) has the potential to improve patient prognosis. This study identified potentially significant metabolites differentiating between breast cancer patients and healthy controls to help in diagnosis, grading, staging and determination of neoadjuvant status. Serum was collected from 152 pre-operative breast cancer (BC) patients and 155 healthy controls in this case-controlled study. Gas chromatography-mass spectrometry (GC-MS) was used to obtain metabolic profiles followed by chemometric analysis with the identification of significantly differentiated metabolites including 7 for diagnosis, 18 for grading, 23 for staging, 15 for stage III subcategory and 10 for neoadjuvant status (p-value < 0...
May 11, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28495347/a-web-based-clinical-decision-support-system-for-gestational-diabetes-automatic-diet-prescription-and-detection-of-insulin-needs
#17
Estefanía Caballero-Ruiz, Gema García-Sáez, Mercedes Rigla, María Villaplana, Belen Pons, M Elena Hernando
BACKGROUND: The growth of diabetes prevalence is causing an increasing demand in health care services which affects the clinicians' workload as medical resources do not grow at the same rate as the diabetic population. Decision support tools can help clinicians with the inspection of monitoring data, providing a preliminary analysis to ease their interpretation and reduce the evaluation time per patient. This paper presents Sinedie, a clinical decision support system designed to manage the treatment of patients with gestational diabetes...
June 2017: International Journal of Medical Informatics
https://www.readbyqxmd.com/read/28494995/high-accuracy-detection-of-airway-obstruction-in-asthma-using-machine-learning-algorithms-and-forced-oscillation-measurements
#18
Jorge L M Amaral, Agnaldo J Lopes, Juliana Veiga, Alvaro C D Faria, Pedro L Melo
BACKGROUND AND OBJECTIVES: The main pathologic feature of asthma is episodic airway obstruction. This is usually detected by spirometry and body plethysmography. These tests, however, require a high degree of collaboration and maximal effort on the part of the patient. There is agreement in the literature that there is a demand of research into new technologies to improve non-invasive testing of lung function. The purpose of this study was to develop automatic classifiers to simplify the clinical use and to increase the accuracy of the forced oscillation technique (FOT) in the diagnosis of airway obstruction in patients with asthma...
June 2017: Computer Methods and Programs in Biomedicine
https://www.readbyqxmd.com/read/28494994/predicting-return-visits-to-the-emergency-department-for-pediatric-patients-applying-supervised-learning-techniques-to-the-taiwan-national-health-insurance-research-database
#19
Ya-Han Hu, Chun-Tien Tai, Solomon Chih-Cheng Chen, Hai-Wei Lee, Sheng-Feng Sung
BACKGROUND AND OBJECTIVE: Return visits (RVs) to the emergency department (ED) consume medical resources and may represent a patient safety issue. The occurrence of unexpected RVs is considered a performance indicator for ED care quality. Because children are susceptible to medical errors and utilize considerable ED resources, knowing the factors that affect RVs in pediatric patients helps improve the quality of pediatric emergency care. METHODS: We collected data on visits made by patients aged ≤18years to EDs from the National Health Insurance Research Database...
June 2017: Computer Methods and Programs in Biomedicine
https://www.readbyqxmd.com/read/28493868/vertical-ground-reaction-force-marker-for-parkinson-s-disease
#20
Md Nafiul Alam, Amanmeet Garg, Tamanna Tabassum Khan Munia, Reza Fazel-Rezai, Kouhyar Tavakolian
Parkinson's disease (PD) patients regularly exhibit abnormal gait patterns. Automated differentiation of abnormal gait from normal gait can serve as a potential tool for early diagnosis as well as monitoring the effect of PD treatment. The aim of current study is to differentiate PD patients from healthy controls, on the basis of features derived from plantar vertical ground reaction force (VGRF) data during walking at normal pace. The current work presents a comprehensive study highlighting the efficacy of different machine learning classifiers towards devising an accurate prediction system...
2017: PloS One
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