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Bayesian probability diagnosis

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https://www.readbyqxmd.com/read/29678059/building-bayesian-networks-from-causal-rules
#1
Karima Sedki, Rosy Tsopra
Bayesian Networks (BNs) are often used for designing diagnosis decision support systems. They are a well-established method for reasoning under uncertainty and making inferences. But, eliciting the probabilities can be tedious and time-consuming especially in medical domain where variables are often related by qualitative terms rather than probabilities. The goal of this paper is to propose a method for eliciting the probabilities required in BNs by using and transforming causal rules which are often used in medicine...
2018: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/29609880/progression-free-survival-with-first-line-endocrine-based-therapies-among-postmenopausal-women-with-hr-her2-metastatic-breast-cancer-a-network-meta-analysis
#2
REVIEW
Rajeev Ayyagari, Derek Tang, Oscar Patterson-Lomba, Zhou Zhou, Jipan Xie, David Chandiwana, Anand A Dalal, Polly Ann Niravath
PURPOSE: The comparative efficacy of endocrine-based therapies (ETs) for hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR+/HER2-) metastatic breast cancer (mBC) is not well characterized. This network meta-analysis (NMA) synthesized available evidence on progression-free survival (PFS) with first-line ETs for postmenopausal HR+/HER2- mBC. METHODS: A systematic literature review identified randomized controlled trials of first-line ETs...
March 30, 2018: Clinical Therapeutics
https://www.readbyqxmd.com/read/29584770/visualizing-the-bayesian-2-test-case-the-effect-of-tree-diagrams-on-medical-decision-making
#3
Karin Binder, Stefan Krauss, Georg Bruckmaier, Jörg Marienhagen
In medicine, diagnoses based on medical test results are probabilistic by nature. Unfortunately, cognitive illusions regarding the statistical meaning of test results are well documented among patients, medical students, and even physicians. There are two effective strategies that can foster insight into what is known as Bayesian reasoning situations: (1) translating the statistical information on the prevalence of a disease and the sensitivity and the false-alarm rate of a specific test for that disease from probabilities into natural frequencies, and (2) illustrating the statistical information with tree diagrams, for instance, or with other pictorial representation...
2018: PloS One
https://www.readbyqxmd.com/read/29575170/random-effects-meta-analysis-of-the-clinical-utility-of-tests-and-prediction-models
#4
L Wynants, R D Riley, D Timmerman, B Van Calster
The use of data from multiple studies or centers for the validation of a clinical test or a multivariable prediction model allows researchers to investigate the test's/model's performance in multiple settings and populations. Recently, meta-analytic techniques have been proposed to summarize discrimination and calibration across study populations. Here, we rather consider performance in terms of net benefit, which is a measure of clinical utility that weighs the benefits of true positive classifications against the harms of false positives...
March 25, 2018: Statistics in Medicine
https://www.readbyqxmd.com/read/29505826/phylogeny-molecular-dating-and-zoogeographic-history-of-the-titi-monkeys-callicebus-pitheciidae-of-eastern-brazil
#5
Jeferson Carneiro, Iracilda Sampaio, José de Sousa E Silva-Júnior, Izeni Farias, Tomas Hrbek, Alcides Pissinatti, Ronylson Silva, Antônio Martins-Junior, Jean Boubli, Stephen Francis Ferrari, Horacio Schneider
The titi monkeys belong to a genus of New World primates endemic to South America, which were recently reclassified in three genera (Cheracebus, Plecturocebus and Callicebus). The genus Callicebus, which currently includes five species, is endemic to eastern Brazil, occurring in the Caatinga, Savanna, and Atlantic Forest biomes. In the present study, we investigated the validity of these species and inferred their phylogenetic relationships, divergence times, and biogeographic patterns based on the molecular analysis of a concatenated sequence of 11 mitochondrial and nuclear DNA markers, derived from 13 specimens...
March 2, 2018: Molecular Phylogenetics and Evolution
https://www.readbyqxmd.com/read/29480983/predicting-the-survival-of-gastric-cancer-patients-using-artificial-and-bayesian-neural-networks
#6
Azam Korhani Kangi, Abbas Bahrampour
Introduction and purpose: In recent years the use of neural networks without any premises for investigation of prognosis in analyzing survival data has increased. Artificial neural networks (ANN) use small processors with a continuous network to solve problems inspired by the human brain. Bayesian neural networks (BNN) constitute a neural-based approach to modeling and non-linearization of complex issues using special algorithms and statistical methods. Gastric cancer incidence is the first and third ranking for men and women in Iran, respectively...
February 26, 2018: Asian Pacific Journal of Cancer Prevention: APJCP
https://www.readbyqxmd.com/read/29411949/discrimination-of-malignant-and-normal-kidney-tissue-with-short-wave-infra-red-dispersive-raman-spectroscopy
#7
Miki Haifler, Isaac Pence, Yu Sun, Alexander Kutikov, Robert G Uzzo, Anita Mahadevan-Jansen, Chetan A Patil
Renal mass biopsy is still controversial due to imperfect accuracy(1). Raman spectroscopy (RS) demonstrated promise as an in vivo real-time, non-destructive diagnostic tool in many malignancies. Short wave infra-red (SWIR) RS has the potential to improve on previous RS systems for renal mass diagnosis. The aim of this study is to evaluate a SWIR RS system in differentiating normal and malignant renal samples Measurements were acquired using a benchtop RS system with excitation wavelength at 1064 nm and an InGaAs array detector...
February 7, 2018: Journal of Biophotonics
https://www.readbyqxmd.com/read/29364118/robust-multicontrast-mri-spleen-segmentation-for-splenomegaly-using-multi-atlas-segmentation
#8
Yuankai Huo, Jiaqi Liu, Zhoubing Xu, Robert L Harrigan, Albert Assad, Richard G Abramson, Bennett A Landman
OBJECTIVE: Magnetic resonance imaging (MRI) is an essential imaging modality in noninvasive splenomegaly diagnosis. However, it is challenging to achieve spleen volume measurement from three-dimensional MRI given the diverse structural variations of human abdomens as well as the wide variety of clinical MRI acquisition schemes. Multi-atlas segmentation (MAS) approaches have been widely used and validated to handle heterogeneous anatomical scenarios. In this paper, we propose to use MAS for clinical MRI spleen segmentation for splenomegaly...
February 2018: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/29334498/evidence-based-interpretation-of-amyloid-%C3%AE-pet-results-a-clinician-s-tool
#9
David Bergeron, Rik Ossenkoppele, Robert Jr Laforce
BACKGROUND: Amyloid-β positron emission tomography (PET) allows for in vivo detection of fibrillar amyloid plaques, a pathologic hallmark of Alzheimer's disease (AD). However, amyloid-β PET interpretation is limited by the imperfect correlation between PET and autopsy, and the fact that it is positive in about 20% to 30% of cognitively normal individuals and non-AD dementias, especially when older or carrying the ε4 allele of apolipoprotein E (ApoE4). When facing a positive amyloid PET, clinicians have to evaluate the probability of a pathologic false positive as well as the probability of amyloid positivity being age-related, comorbid to a primary non-AD dementia (clinicopathologic false positive)...
January 2018: Alzheimer Disease and Associated Disorders
https://www.readbyqxmd.com/read/29242838/a-dirichlet-multinomial-bayes-classifier-for-disease-diagnosis-with-microbial-compositions
#10
Xiang Gao, Huaiying Lin, Qunfeng Dong
Dysbiosis of microbial communities is associated with various human diseases, raising the possibility of using microbial compositions as biomarkers for disease diagnosis. We have developed a Bayes classifier by modeling microbial compositions with Dirichlet-multinomial distributions, which are widely used to model multicategorical count data with extra variation. The parameters of the Dirichlet-multinomial distributions are estimated from training microbiome data sets based on maximum likelihood. The posterior probability of a microbiome sample belonging to a disease or healthy category is calculated based on Bayes' theorem, using the likelihood values computed from the estimated Dirichlet-multinomial distribution, as well as a prior probability estimated from the training microbiome data set or previously published information on disease prevalence...
November 2017: MSphere
https://www.readbyqxmd.com/read/29216851/what-does-igra-testing-add-to-the-diagnosis-of-ocular-tuberculosis-a-bayesian-latent-class-analysis
#11
Rupesh Agrawal, Robert Grant, Bhaskar Gupta, Dinesh Visva Gunasekeran, Julio J Gonzalez-Lopez, Peter K F Addison, Mark Westcott, Carlos E Pavesio
BACKGROUND: To evaluate the contribution made to the diagnostic work-up for patients with suspected ocular tuberculosis (TB) by QuantiFERON-TB Gold In-Tube (QFT) tests using latent class analysis model. METHODS: A single centre retrospective cohort study. A Bayesian latent class model was constructed on the basis of demographics, phenotypes and test results from patients attending a tertiary referral center in the UK. This estimated the probability of ocular TB for each patient in two versions, first with and then without QFT...
December 8, 2017: BMC Ophthalmology
https://www.readbyqxmd.com/read/29121922/assisting-differential-clinical-diagnosis-of-cattle-diseases-using-smartphone-based-technology-in-low-resource-settings-a-pilot-study
#12
Tariku Jibat Beyene, Amanuel Eshetu, Amina Abdu, Etenesh Wondimu, Ashenafi Feyisa Beyi, Takele Beyene Tufa, Sami Ibrahim, Crawford W Revie
BACKGROUND: The recent rise in mobile phone use and increased signal coverage has created opportunities for growth of the mobile Health sector in many low resource settings. This pilot study explores the use of a smartphone-based application, VetAfrica-Ethiopia, in assisting diagnosis of cattle diseases. We used a modified Delphi protocol to select important diseases and Bayesian algorithms to estimate the related disease probabilities based on various clinical signs being present in Ethiopian cattle...
November 9, 2017: BMC Veterinary Research
https://www.readbyqxmd.com/read/29091206/dynamics-and-phylogenetic-relationships-of-hiv-1-transmitted-drug-resistance-according-to-subtype-in-italy-over-the-years-2000-14
#13
L Fabeni, C Alteri, D Di Carlo, N Orchi, L Carioti, A Bertoli, C Gori, F Forbici, F Continenza, G Maffongelli, C Pinnetti, A Vergori, A Mondi, A Ammassari, V Borghi, M Giuliani, G De Carli, S Pittalis, S Grisetti, A Pennica, C M Mastroianni, F Montella, A Cristaudo, C Mussini, E Girardi, M Andreoni, A Antinori, F Ceccherini-Silberstein, C F Perno, M M Santoro
Background: Transmitted drug-resistance (TDR) remains a critical aspect for the management of HIV-1-infected individuals. Thus, studying the dynamics of TDR is crucial to optimize HIV care. Methods: In total, 4323 HIV-1 protease/reverse-transcriptase sequences from drug-naive individuals diagnosed in north and central Italy between 2000 and 2014 were analysed. TDR was evaluated over time. Maximum-likelihood and Bayesian phylogenetic trees with bootstrap and Bayesian-probability supports defined transmission clusters...
October 1, 2017: Journal of Antimicrobial Chemotherapy
https://www.readbyqxmd.com/read/29059331/automated-influenza-case-detection-for-public-health-surveillance-and-clinical-diagnosis-using-dynamic-influenza-prevalence-method
#14
Fuchiang Tsui, Y Ye, Victor Ruiz, Gregory F Cooper, Michael M Wagner
Objectives: To assess the performance of a Bayesian case detector (BCD) for influenza surveillance and clinical diagnosis. Methods: BCD uses a Bayesian network classifier to compute the posterior probability of a patient having influenza based on 31 findings from narrative clinical notes. To assess the potential for disease surveillance, we calculated area under the receiver operating characteristic curve (AUC) to indicate BCD's ability to differentiate between influenza and non-influenza encounters in emergency department settings...
October 20, 2017: Journal of Public Health
https://www.readbyqxmd.com/read/29032721/estimation-of-sensitivity-and-specificity-of-pregnancy-diagnosis-using-transrectal-ultrasonography-and-elisa-for-pregnancy-associated-glycoprotein-in-dairy-cows-using-a-bayesian-latent-class-model
#15
R W Shephard, J M Morton
AIMS: To determine the sensitivity (Se) and specificity (Sp) of pregnancy diagnosis using transrectal ultrasonography and an ELISA for pregnancy-associated glycoprotein (PAG) in milk, in lactating dairy cows in seasonally calving herds approximately 85-100 days after the start of the herd's breeding period. METHODS: Paired results were used from pregnancy diagnosis using transrectal ultrasonography and ELISA for PAG in milk carried out approximately 85 and 100 days after the start of the breeding period, respectively, from 879 cows from four herds in Victoria, Australia...
January 2018: New Zealand Veterinary Journal
https://www.readbyqxmd.com/read/29030419/accuracy-of-clinical-diagnosis-of-dementia-with-lewy-bodies-a-systematic-review-and-meta-analysis
#16
Giovanni Rizzo, Simona Arcuti, Massimiliano Copetti, Maria Alessandria, Rodolfo Savica, Andrea Fontana, Rocco Liguori, Giancarlo Logroscino
BACKGROUND: The diagnosis of dementia with Lewy bodies (DLB) is based on diagnostic clinical criteria, which were updated over the years. OBJECTIVE: To evaluate, through a systematic review, accuracy of the diagnostic criteria, testing a possible improvement over time. METHODS: We searched on MEDLINE and SCOPUS databases for studies reporting diagnostic parameters regarding the clinical diagnosis of DLB until October 2016. We performed meta-analysis, using a Bayesian approach, on those using pathological examination as gold standard, subclassified based on the different diagnostic criteria used...
October 13, 2017: Journal of Neurology, Neurosurgery, and Psychiatry
https://www.readbyqxmd.com/read/29029359/a-probabilistic-network-for-the-diagnosis-of-acute-cardiopulmonary-diseases
#17
Alessandro Magrini, Davide Luciani, Federico M Stefanini
In this paper, the development of a probabilistic network for the diagnosis of acute cardiopulmonary diseases is presented in detail. A panel of expert physicians collaborated to specify the qualitative part, which is a directed acyclic graph defining a factorization of the joint probability distribution of domain variables into univariate conditional distributions. The quantitative part, which is a set of parametric models defining these univariate conditional distributions, was estimated following the Bayesian paradigm...
January 2018: Biometrical Journal. Biometrische Zeitschrift
https://www.readbyqxmd.com/read/29020131/data-adaptive-estimation-for-double-robust-methods-in-population-based-cancer-epidemiology-risk-differences-for-lung-cancer-mortality-by-emergency-presentation
#18
Miguel Angel Luque-Fernandez, Aurélien Belot, Linda Valeri, Giovanni Ceruli, Camille Maringe, Bernard Rachet
We propose a structural framework for population-based cancer epidemiology and evaluate the performance of double-robust estimators for a binary exposure in cancer mortality. We performed numerical analyses to study the bias and efficiency of these estimators. Furthermore, we compared two different model selection strategies based on 1) the Akaike and Bayesian Information Criteria and 2) machine-learning algorithms, and illustrated double-robust estimators' performance in a real setting. In simulations with correctly specified models and near-positivity violations, all but the naïve estimators presented relatively good performance...
September 11, 2017: American Journal of Epidemiology
https://www.readbyqxmd.com/read/28988525/the-role-of-biofilm-forming-on-mortality-in-patients-with-candidemia-a-study-derived-from-real-world-data
#19
Carlo Tascini, Emanuela Sozio, Laura Corte, Francesco Sbrana, Claudio Scarparo, Andrea Ripoli, Giacomo Bertolino, Maria Merelli, Enrico Tagliaferri, Antonio Corcione, Matteo Bassetti, Gianluigi Cardinali, Francesco Menichetti
BACKGROUND: Evaluation of the role on patient mortality exerted by biofilm forming (BF) Candida strains, by using predictive clinical data. METHODS: Eighty-nine strains isolated from Candida bloodstream infection, occurring in two Italian University Hospitals, were employed in this study. A random forest (RF) model was built with a procedure of iterative selection of the risk factors potentially able to predict the probability of death. The similarity between patient conditions and Bayesian clustering was calculated in order to evaluate the role of predictors in the stratification of the death risk...
October 9, 2017: Infectious Diseases
https://www.readbyqxmd.com/read/28941736/a-prognostic-tool-to-predict-outcomes-in-children-undergoing-the-norwood-operation
#20
Punkaj Gupta, Avishek Chakraborty, Jeffrey M Gossett, Mallikarjuna Rettiganti
OBJECTIVES: To create and validate a prediction model to assess outcomes associated with the Norwood operation. METHODS: The public-use dataset from a multicenter, prospective, randomized single-ventricle reconstruction trial was used to create this novel prediction tool. A Bayesian lasso logistic regression model was used for variable selection. We used a hierarchical framework by representing discrete probability models with continuous latent variables that depended on the risk factors for a particular patient...
December 2017: Journal of Thoracic and Cardiovascular Surgery
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