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https://www.readbyqxmd.com/read/29669499/qsar-study-of-some-1-3-oxazolylphosphonium-derivatives-as-new-potent-anti-candida-agents-and-their-toxicity-evaluation
#1
Maria M Trush, Vasyl Kovalishyn, Alla D Ocheretniuk, Oleksandr L Kobzar, Maryna V Kachaeva, Volodymyr S Brovarets, Larisa O Metelytsia
This paper describes QSAR studies by using the Online Chemical Modeling Environment, synthesis, in vitro antifungal activity of 1,3-oxazolylphosphonium derivatives and their acetylcholinesterase inhibitory potential. Three classification QSAR models were created using Random Forests (WEKA-RF), k-Nearest Neighbors and Associative Neural Networks methods and different combinations of descriptors. The predictive ability of the models was tested through cross-validation, giving a balanced accuracy BA=80-91%. All compounds demonstrated good antifungal properties and slight inhibition of acetylcholinesterase activity...
April 18, 2018: Current Drug Discovery Technologies
https://www.readbyqxmd.com/read/29518921/analysis-of-occupational-accidents-in-underground-and-surface-mining-in-spain-using-data-mining-techniques
#2
Lluís Sanmiquel, Marc Bascompta, Josep M Rossell, Hernán Francisco Anticoi, Eduard Guash
An analysis of occupational accidents in the mining sector was conducted using the data from the Spanish Ministry of Employment and Social Safety between 2005 and 2015, and data-mining techniques were applied. Data was processed with the software Weka. Two scenarios were chosen from the accidents database: surface and underground mining. The most important variables involved in occupational accidents and their association rules were determined. These rules are composed of several predictor variables that cause accidents, defining its characteristics and context...
March 7, 2018: International Journal of Environmental Research and Public Health
https://www.readbyqxmd.com/read/29503750/comparison-of-models-for-the-prediction-of-medical-costs-of-spinal-fusion-in-taiwan-diagnosis-related-groups-by-machine-learning-algorithms
#3
Ching-Yen Kuo, Liang-Chin Yu, Hou-Chaung Chen, Chien-Lung Chan
Objectives: The aims of this study were to compare the performance of machine learning methods for the prediction of the medical costs associated with spinal fusion in terms of profit or loss in Taiwan Diagnosis-Related Groups (Tw-DRGs) and to apply these methods to explore the important factors associated with the medical costs of spinal fusion. Methods: A data set was obtained from a regional hospital in Taoyuan city in Taiwan, which contained data from 2010 to 2013 on patients of Tw-DRG49702 (posterior and other spinal fusion without complications or comorbidities)...
January 2018: Healthcare Informatics Research
https://www.readbyqxmd.com/read/29494924/imidazolium-ionic-liquids-as-effective-antiseptics-and-disinfectants-against-drug-resistant-s-aureus-in-silico-and-in-vitro-studies
#4
Diana Hodyna, Vasyl Kovalishyn, Ivan Semenyuta, Volodymyr Blagodatnyi, Sergiy Rogalsky, Larisa Metelytsia
This paper describes Quantitative Structure-Activity Relationships (QSAR) studies, molecular docking and in vitro antibacterial activity of several potent imidazolium-based ionic liquids (ILs) against S. aureus ATCC 25923 and its clinical isolate. Small set of 131 ILs was collected from the literature and uploaded in the OCHEM database. QSAR methodologies used Associative Neural Networks and Random Forests (WEKA-RF) methods. The predictive ability of the models was tested through cross-validation, giving cross-validated coefficients q2  = 0...
April 2018: Computational Biology and Chemistry
https://www.readbyqxmd.com/read/29342870/biomarkers-of-progression-after-hiv-acute-early-infection-nothing-compares-to-cd4%C3%A2-%C2%BA-t-cell-count
#5
Gabriela Turk, Yanina Ghiglione, Macarena Hormanstorfer, Natalia Laufer, Romina Coloccini, Jimena Salido, César Trifone, María Julia Ruiz, Juliana Falivene, María Pía Holgado, María Paula Caruso, María Inés Figueroa, Horacio Salomón, Luis D Giavedoni, María de Los Ángeles Pando, María Magdalena Gherardi, Roberto Daniel Rabinovich, Pedro A Pury, Omar Sued
Progression of HIV infection is variable among individuals, and definition disease progression biomarkers is still needed. Here, we aimed to categorize the predictive potential of several variables using feature selection methods and decision trees. A total of seventy-five treatment-naïve subjects were enrolled during acute/early HIV infection. CD4⁺ T-cell counts (CD4TC) and viral load (VL) levels were determined at enrollment and for one year. Immune activation, HIV-specific immune response, Human Leukocyte Antigen (HLA) and C-C chemokine receptor type 5 (CCR5) genotypes, and plasma levels of 39 cytokines were determined...
January 13, 2018: Viruses
https://www.readbyqxmd.com/read/29284916/comparison-of-basic-and-ensemble-data-mining-methods-in-predicting-5-year-survival-of-colorectal-cancer-patients
#6
Mohamad Amin Pourhoseingholi, Sedigheh Kheirian, Mohammad Reza Zali
Introduction: Colorectal cancer (CRC) is one of the most common malignancies and cause of cancer mortality worldwide. Given the importance of predicting the survival of CRC patients and the growing use of data mining methods, this study aims to compare the performance of models for predicting 5-year survival of CRC patients using variety of basic and ensemble data mining methods. Methods: The CRC dataset from The Shahid Beheshti University of Medical Sciences Research Center for Gastroenterology and Liver Diseases were used for prediction and comparative study of the base and ensemble data mining techniques...
December 2017: Acta Informatica Medica: AIM
https://www.readbyqxmd.com/read/29279441/data-mining-and-machine-learning-algorithms-using-il28b-genotype-and-biochemical-markers-best-predicted-advanced-liver-fibrosis-in-chronic-hepatitis-c
#7
Hend Ibrahim Shousha, Abubakr Hussein Awad, Dalia Abdelhamid Omran, Mayada Mohamed Elnegouly, Mahasen Mabrouk
IL28B single nucleotide polymorphism (rs12979860) is an etiology-independent predictor of hepatitis C virus (HCV)-related hepatic fibrosis. Data mining is a method of predictive analysis which can explore tremendous volumes of information from health records to discover hidden patterns and relationships. The current study aims to evaluate and compare the prediction accuracy of scoring system like aspartate aminotransferase-to-platelet ratio index (APRI) and fibrosis-4 (FIB-4) index versus data mining for the prediction of HCV-related advanced fibrosis...
January 23, 2018: Japanese Journal of Infectious Diseases
https://www.readbyqxmd.com/read/29249345/analysis-and-multiclass-classification-of-pathological-knee-joints-using-vibroarthrographic-signals
#8
Krzysztof Kręcisz, Dawid Bączkowicz
BACKGROUND AND OBJECTIVE: Vibroarthrography (VAG) is a method developed for sensitive and objective assessment of articular function. Although the VAG method is still in development, it shows high accuracy, sensitivity and specificity when comparing results obtained from controls and the non-specific, knee-related disorder group. However, the multiclass classification remains practically unknown. Therefore the aim of this study was to extend the VAG method classification to 5 classes, according to different disorders of the patellofemoral joint...
February 2018: Computer Methods and Programs in Biomedicine
https://www.readbyqxmd.com/read/29241659/a-novel-method-for-predicting-kidney-stone-type-using-ensemble-learning
#9
Yassaman Kazemi, Seyed Abolghasem Mirroshandel
The high morbidity rate associated with kidney stone disease, which is a silent killer, is one of the main concerns in healthcare systems all over the world. Advanced data mining techniques such as classification can help in the early prediction of this disease and reduce its incidence and associated costs. The objective of the present study is to derive a model for the early detection of the type of kidney stone and the most influential parameters with the aim of providing a decision-support system. Information was collected from 936 patients with nephrolithiasis at the kidney center of the Razi Hospital in Rasht from 2012 through 2016...
January 2018: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/29188115/raman-spectral-post-processing-for-oral-tissue-discrimination-a-step-for-an-automatized-diagnostic-system
#10
Luis Felipe C S Carvalho, Marcelo Saito Nogueira, Lázaro P M Neto, Tanmoy T Bhattacharjee, Airton A Martin
Most oral injuries are diagnosed by histopathological analysis of a biopsy, which is an invasive procedure and does not give immediate results. On the other hand, Raman spectroscopy is a real time and minimally invasive analytical tool with potential for the diagnosis of diseases. The potential for diagnostics can be improved by data post-processing. Hence, this study aims to evaluate the performance of preprocessing steps and multivariate analysis methods for the classification of normal tissues and pathological oral lesion spectra...
November 1, 2017: Biomedical Optics Express
https://www.readbyqxmd.com/read/29167776/prognosis-and-early-diagnosis-of-ductal-and-lobular-type-in-breast-cancer-patient
#11
Houriyeh Ehtemam, Mitra Montazeri, Reza Khajouei, Raziyeh Hosseini, Ali Nemati, Vahid Maazed
Background: Breast cancer is one of the most common cancers with a high mortality rate among women. Prognosis and early diagnosis of breast cancer among women society reduce considerable rate of their mortality. Nowadays, due to this illness, try to be setting up intelligent systems, which can predict and early diagnose this cancer, and reduce mortality of women society. Methods: Overall, 208 samples were collected from 2014 to 2015 from two oncologist offices and Javadalaemeh Clinic in Kerman, southeastern Iran...
November 2017: Iranian Journal of Public Health
https://www.readbyqxmd.com/read/29075939/web-enabled-distributed-health-care-framework-for-automated-malaria-parasite-classification-an-e-health-approach
#12
Maitreya Maity, Dhiraj Dhane, Tushar Mungle, A K Maiti, Chandan Chakraborty
Web-enabled e-healthcare system or computer assisted disease diagnosis has a potential to improve the quality and service of conventional healthcare delivery approach. The article describes the design and development of a web-based distributed healthcare management system for medical information and quantitative evaluation of microscopic images using machine learning approach for malaria. In the proposed study, all the health-care centres are connected in a distributed computer network. Each peripheral centre manages its' own health-care service independently and communicates with the central server for remote assistance...
October 26, 2017: Journal of Medical Systems
https://www.readbyqxmd.com/read/29054255/predicting-cd4-count-changes-among-patients-on-antiretroviral-treatment-application-of-data-mining-techniques
#13
Mihiretu Kebede, Desalegn Tigabu Zegeye, Berihun Megabiaw Zeleke
BACKGROUND AND OBJECTIVES: To monitor the progress of therapy and disease progression, periodic CD4 counts are required throughout the course of HIV/AIDS care and support. The demand for CD4 count measurement is increasing as ART programs expand over the last decade. This study aimed to predict CD4 count changes and to identify the predictors of CD4 count changes among patients on ART. METHODS: A cross-sectional study was conducted at the University of Gondar Hospital from 3,104 adult patients on ART with CD4 counts measured at least twice (baseline and most recent)...
December 2017: Computer Methods and Programs in Biomedicine
https://www.readbyqxmd.com/read/28828993/general-machine-learning-model-review-and-experimental-theoretic-study-of-magnolol-activity-in-enterotoxigenic-induced-oxidative-stress
#14
REVIEW
Yanli Deng, Yong Liu, Shaoxun Tang, Chuanshe Zhou, Xuefeng Han, Wenjun Xiao, Lucas Anton Pastur-Romay, Jose Manuel Vazquez-Naya, Javier Pereira Loureiro, Cristian R Munteanu, Zhiliang Tan
This study evaluated the antioxidative effects of magnolol based on the mouse model induced by Enterotoxigenic Escherichia coli (E. coli, ETEC). All experimental mice were equally treated with ETEC suspensions (3.45×109 CFU/ml) after oral administration of magnolol for 7 days at the dose of 0, 100, 300 and 500 mg/kg Body Weight (BW), respectively. The oxidative metabolites and antioxidases for each sample (organism of mouse) were determined: Malondialdehyde (MDA), Nitric Oxide (NO), Glutathione (GSH), Myeloperoxidase (MPO), Catalase (CAT), Superoxide Dismutase (SOD), and Glutathione Peroxidase (GPx)...
2017: Current Topics in Medicinal Chemistry
https://www.readbyqxmd.com/read/28805283/closing-the-gap-avian-lineage-splits-at-a-young-narrow-seaway-imply-a-protracted-history-of-mixed-population-response
#15
Steve A Trewick, Stephen Pilkington, Lara D Shepherd, Gillian C Gibb, Mary Morgan-Richards
The evolutionary significance of spatial habitat gaps has been well recognized since Alfred Russel Wallace compared the faunas of Bali and Lombok. Gaps between islands influence population structuring of some species, and flightless birds are expected to show strong partitioning even where habitat gaps are narrow. We examined the population structure of the most numerous living flightless land bird in New Zealand, Weka (Gallirallus australis). We surveyed Weka and their feather lice in native and introduced populations using genetic data gathered from DNA sequences of mitochondrial genes and nuclear β-fibrinogen and five microsatellite loci...
October 2017: Molecular Ecology
https://www.readbyqxmd.com/read/28802948/modelling-the-toxicity-of-a-large-set-of-metal-and-metal-oxide-nanoparticles-using-the-ochem-platform
#16
Vasyl Kovalishyn, Natalia Abramenko, Iryna Kopernyk, Larysa Charochkina, Larysa Metelytsia, Igor V Tetko, Willie Peijnenburg, Leonid Kustov
Inorganic nanomaterials have become one of the new areas of modern knowledge and technology and have already found an increasing number of applications. However, some nanoparticles show toxicity to living organisms, and can potentially have a negative influence on environmental ecosystems. While toxicity can be determined experimentally, such studies are time consuming and costly. Computational toxicology can provide an alternative approach and there is a need to develop methods to reliably assess Quantitative Structure-Property Relationships for nanomaterials (nano-QSPRs)...
February 2018: Food and Chemical Toxicology
https://www.readbyqxmd.com/read/28658883/artificial-neural-network-ann-model-to-predict-depression-among-geriatric-population-at-a-slum-in-kolkata-india
#17
Arkaprabha Sau, Ishita Bhakta
INTRODUCTION: Depression is one of the most important causes of mortality and morbidity among the geriatric population. Although, the aging brain is more vulnerable to depression, it cannot be considered as physiological and an inevitable part of ageing. Various sociodemographic and morbidity factors are responsible for the depression among them. Using Artificial Neural Network (ANN) model depression can be predicted from various sociodemographic variables and co morbid conditions even at community level by the grass root level health care workers...
May 2017: Journal of Clinical and Diagnostic Research: JCDR
https://www.readbyqxmd.com/read/28369169/trainable-weka-segmentation-a-machine-learning-tool-for-microscopy-pixel-classification
#18
Ignacio Arganda-Carreras, Verena Kaynig, Curtis Rueden, Kevin W Eliceiri, Johannes Schindelin, Albert Cardona, H Sebastian Seung
Summary: State-of-the-art light and electron microscopes are capable of acquiring large image datasets, but quantitatively evaluating the data often involves manually annotating structures of interest. This process is time-consuming and often a major bottleneck in the evaluation pipeline. To overcome this problem, we have introduced the Trainable Weka Segmentation (TWS), a machine learning tool that leverages a limited number of manual annotations in order to train a classifier and segment the remaining data automatically...
August 1, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28292249/a-feature-and-algorithm-selection-method-for-improving-the-prediction-of-protein-structural-class
#19
Qianwu Ni, Lei Chen
AIM AND OBJECTIVE: Correct prediction of protein structural class is beneficial to investigation on protein functions, regulations and interactions. In recent years, several computational methods have been proposed in this regard. However, based on various features, it is still a great challenge to select proper classification algorithm and extract essential features to participate in classification. MATERIAL AND METHODS: In this study, a feature and algorithm selection method was presented for improving the accuracy of protein structural class prediction...
2017: Combinatorial Chemistry & High Throughput Screening
https://www.readbyqxmd.com/read/28269470/can-we-make-a-carpet-smart-enough-to-detect-falls
#20
Fadi Muheidat, Harry W Tyrer
In this paper, we have enhanced smart carpet, which is a floor based personnel detector system, to detect falls using a faster but low cost processor. Our hardware front end reads 128 sensors, with sensors output a voltage due to a person walking or falling on the carpet. The processor is Jetson TK1, which provides more computing power than before. We generated a dataset with volunteers who walked and fell to test our algorithms. Data obtained allowed examining data frames (a frame is a single scan of the carpet sensors) read from the data acquisition system...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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