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36961por Lemos, Moara, Fermino, Bruno R., Simas-Rodrigues, Cíntia, Hoffmann, Luísa, Silva, Rosane, Camargo, Erney P., Teixeira, Marta M. G., Souto-Padrón, Thaïs“…Trypanosoma abeli n. sp. is highly prevalent in H. luetkeni and H. affinis armoured catfish from the Atlantic Forest biome, and in other catfish species from the Amazon and the Pantanal. …”
Publicado 2015
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36962por Pellatt, Daniel F, Stevens, John R, Wolff, Roger K, Mullany, Lila E, Herrick, Jennifer S, Samowitz, Wade, Slattery, Martha L“…Agilent Human miRNA Microarray V.19.0 was used to generate miRNA expression profiles; validation of expression levels was carried out using quantitative PCR. We used random forest analysis and verified findings with logistic modeling in separate data sets. …”
Publicado 2016
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36963por Coombs, Nathan J, Coombs, Joel M, Vaidya, Uma J, Singer, Julian, Bulsara, Max, Tobias, Jeffrey S, Wenz, Frederik, Joseph, David J, Brown, Douglas A, Rainsbury, Richard, Davidson, Tim, Adamson, Douglas J A, Massarut, Samuele, Morgan, David, Potyka, Ingrid, Corica, Tammy, Falzon, Mary, Williams, Norman, Baum, Michael, Vaidya, Jayant S“…If widely available, 5 million miles (8 000 000 km) of travel, 170 000 woman-hours and 1200 tonnes of CO(2) (a forest of 100 hectares) will be saved annually in the UK. …”
Publicado 2016
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36964por Dafaalla, Mohamed D, Nimir, Mohammed N, Mohammed, Mosab I, Ali, Omer A, Hussein, Abbashar“…Our risk factors of interest were age, sex, duration of diabetes, body mass index (BMI), systolic blood pressure (sBP) and diastolic blood pressure (dBP), glycated haemoglobin (HbA1c), high-density lipoprotein and low-density lipoprotein (HDL and LDL), triglycerides, retinopathy and nephropathy. We generated Forest plots, χ(2) test and I(2) as tests for heterogeneity, risk ratio (RR), mean difference (MD), CIs and p values by ReVMan V.5.3 software. …”
Publicado 2016
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36965por Auguste, Peter, Tsertsvadze, Alexander, Pink, Joshua, Court, Rachel, McCarthy, Noel, Sutcliffe, Paul, Clarke, Aileen“…In immunocompromised people, IGRA (T-SPOT.TB) was not significant different from TST (≥10 mm) for identifying LTBI, (pooled R-CIR = 1.01, 95% CI: 0.65, 1.58). The forest plot of two studies in recently arrived people from countries with high TB burden demonstrated inconsistent findings (high heterogeneity; I(2) = 92%). …”
Publicado 2017
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36966por Siriwardhana, Chathura, Fang, Rui, Salanti, Ali, Leke, Rose G. F., Bobbili, Naveen, Taylor, Diane Wallace, Chen, John J.“…Ab levels along with clinical variables (age, gravidity) were used in the following seven statistical approaches: logistic regression full model, logistic regression reduced model, recursive partitioning, random forests, linear discriminant analysis, quadratic discriminant analysis, and support vector machine. …”
Publicado 2017
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36967por Kwenti, Tebit Emmanuel, Moye, Adzemye Linus, Wiylanyuy, Adzemye Basil, Njunda, Longdoh Anna, Nkuo-Akenji, Theresa“…METHODS: In a cross-sectional survey performed between April and July 2015, 602 children between 2 and 15 years (mean ± SD = 5.7 ± 3.7), comprising 319 (53%) males were enrolled from five epidemiological strata of malaria in Cameroon including: the sudano-sahelian (SS) strata, the high inland plateau (HIP) strata, the south Cameroonian equatorial forest (SCEF) strata, the high western plateau (HWP) strata, and the coastal (C) strata. …”
Publicado 2017
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36968por Low, Carissa A, Dey, Anind K, Ferreira, Denzil, Kamarck, Thomas, Sun, Weijing, Bae, Sangwon, Doryab, Afsaneh“…We used a rotation random forests classifier with cross-validation and resampling with replacement to evaluate population and individual model performance and correlation-based feature subset selection to select nonredundant features with the best predictive ability. …”
Publicado 2017
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36969por Adhikari, Bipin, Phommasone, Koukeo, Kommarasy, Palingnaphone, Soundala, Xayaphone, Souvanthong, Phonesavanh, Pongvongsa, Tiengkham, Henriques, Gisela, Newton, Paul N., White, Nicholas J., Day, Nicholas P. J., Dondorp, Arjen M., von Seidlein, Lorenz, Mayxay, Mayfong, Cheah, Phaik Yeong, Pell, Christopher“…The risk of malaria including asymptomatic infection was explained in terms of participants’ work in forest and fields, and poor hygiene. During the MDA rounds, there was an improvement in knowledge on the concept of asymptomatic malaria, the rationale of MDA and the blood test. …”
Publicado 2018
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36970por Masello, Juan F., Martínez, Javier, Calderón, Luciano, Wink, Michael, Quillfeldt, Petra, Sanz, Virginia, Theuerkauf, Jörn, Ortiz-Catedral, Luis, Berkunsky, Igor, Brunton, Dianne, Díaz-Luque, José A., Hauber, Mark E., Ojeda, Valeria, Barnaud, Antoine, Casalins, Laura, Jackson, Bethany, Mijares, Alfredo, Rosales, Romel, Seixas, Gláucia, Serafini, Patricia, Silva-Iturriza, Adriana, Sipinski, Elenise, Vásquez, Rodrigo A., Widmann, Peter, Widmann, Indira, Merino, Santiago“…Individuals from open habitats were less infected than those from forests. CONCLUSIONS: The consumption of food items known for their secondary metabolites with antimalarial, trypanocidal or general antiparasitic properties, as well as the higher proportion of infected species among omnivorous parrots, could explain the low prevalence of hemoparasites reported in many vertebrates. …”
Publicado 2018
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36971por Marquez, Christine, Johnson, Alekhya Mascarenhas, Jassemi, Sabrina, Park, Jamie, Moore, Julia E., Blaine, Caroline, Bourdon, Gertrude, Chignell, Mark, Ellen, Moriah E., Fortin, Jacques, Graham, Ian D., Hayes, Anne, Hamid, Jemila, Hemmelgarn, Brenda, Hillmer, Michael, Holmes, Bev, Holroyd-Leduc, Jayna, Hubert, Linda, Hutton, Brian, Kastner, Monika, Lavis, John N., Michell, Karen, Moher, David, Ouimet, Mathieu, Perrier, Laure, Proctor, Andrea, Noseworthy, Thomas, Schuckel, Victoria, Stayberg, Sharlene, Tonelli, Marcello, Tricco, Andrea C., Straus, Sharon E.“…HCMs preferred a traditional information order (i.e., methods, study flow diagram, forest plots) whereas PMs preferred an alternative order (i.e., background and key messages on one page; methods and limitations on another). …”
Publicado 2018
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36972por Pongvongsa, Tiengkham, Phommasone, Koukeo, Adhikari, Bipin, Henriques, Gisela, Chotivanich, Kesinee, Hanboonkunupakarn, Borimas, Mukaka, Mavuto, Peerawaranun, Pimnara, von Seidlein, Lorenz, Day, Nicholas P. J., White, Nicholas J., Dondorp, Arjen M., Imwong, Mallika, Newton, Paul N., Singhasivanon, Pratap, Mayxay, Mayfong, Pukrittayakamee, Sasithon“…MDAs must be integrated in multi-pronged approaches such as vector control and preventive measures with a focus on specific risk groups such as mobile, migrant population and forest goers for a sustained period to eliminate the remaining parasite reservoirs. …”
Publicado 2018
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36973por Lee, Kyoung Hwa, Yoo, Seul Gi, Kwon, Da Eun, Park, Soon Young, Dong, Jae June, Chae, Myunghun, Min, Choongki, Kang, Jaewoo, Song, Young Goo“…The primary outcome was bacteremia, and the training data were analyzed to make prediction model with conventional Bayesian approach, Support Vector Machine (SVM), Random Forest (RF) and multi-layer perceptron (MLP), a representative artificial neural network (ANN) model, respectively. …”
Publicado 2018
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36974por Kim, Hosung, Kang, Woo Seok, Park, Hong Ju, Lee, Jee Yeon, Park, Jun Woo, Kim, Yehree, Seo, Ji Won, Kwak, Min Young, Kang, Byung Chul, Yang, Chan Joo, Duffy, Ben A., Cho, Young Sang, Lee, Sang-Youp, Suh, Myung Whan, Moon, Il Joon, Ahn, Joong Ho, Cho, Yang-Sun, Oh, Seung Ha, Chung, Jong Woo“…For postlingually deaf adults (n de120) who received CI with full insertion, we predicted CI outcomes using a Random-Forest Regression (RFR) model and investigated the effect of preoperative factors on CI outcomes. …”
Publicado 2018
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36975por Patnaik, Bharat Bhusan, Chung, Jong Min, Hwang, Hee Ju, Sang, Min Kyu, Park, Jie Eun, Min, Hye Rin, Cho, Hang Chul, Dewangan, Neha, Baliarsingh, Snigdha, Kang, Se Won, Park, So Young, Jo, Yong Hun, Park, Hong Seog, Kim, Wan Jong, Han, Yeon Soo, Lee, Jun Sang, Lee, Yong Seok“…The species is on a decline due to depletion of forest cover, predation by natural enemies, and collection. …”
Publicado 2019
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36976por Sales, Kamila Gaudêncio da Silva, de Oliveira Miranda, Débora Elienai, Costa, Pietra Lemos, da Silva, Fernando José, Figueredo, Luciana Aguiar, Brandão-Filho, Sinval Pinto, Dantas-Torres, Filipe“…The adaptation of sand flies to the indoor environment in the studied indigenous villages may be partly explained by the poor housing conditions and the proximity of the houses to crop plantations and forest fragments. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13071-019-3383-1) contains supplementary material, which is available to authorized users.…”
Publicado 2019
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36977“…We collected Instagram posts using a Web scraper between July 2018 and October 2018 and then compared our deep learning model against 3 different machine learning models (eg, random forest, decision tree, and support vector machine) to assess the performance and accuracy of the model. …”
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36978por Hao, Yiming, Cheng, Feng, Pham, Minh, Rein, Hayley, Patel, Devashru, Fang, Yuchen, Feng, Yiyi, Yan, Jin, Song, Xueyang, Yan, Haixia, Wang, Yiqin“…Various machine learning models such as linear discriminant analysis, support vector machines (SVMs), and random forests were applied to classify the control group, diabetic patients, and diabetic patients with complications. …”
Publicado 2019
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36979por Mukherjee, Sabyasachi, Cai, Zexi, Mukherjee, Anupama, Longkumer, Imsusosang, Mech, Moonmoon, Vupru, Kezhavituo, Khate, Kobu, Rajkhowa, Chandan, Mitra, Abhijit, Guldbrandtsen, Bernt, Lund, Mogens Sandø, Sahana, Goutam“…BACKGROUND: Mithun (Bos frontalis), also called gayal, is an endangered bovine species, under the tribe bovini with 2n = 58 XX chromosome complements and reared under the tropical rain forests region of India, China, Myanmar, Bhutan and Bangladesh. …”
Publicado 2019
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36980“…The wearable and RAI-HC assessment data were analyzed and utilized to create fall risk classification models, with 3 supervised machine learning algorithms: logistic regression, decision tree, and random forest (RF). RESULTS: Of 40 participants aged 65 to 93 years, 16 (40%) had no previous falls, whereas 8 (20%) and 16 (40%) had experienced 1 and multiple (≥2) falls, respectively. …”
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