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Bayesian probability diagnosis

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https://www.readbyqxmd.com/read/29029359/a-probabilistic-network-for-the-diagnosis-of-acute-cardiopulmonary-diseases
#1
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...
October 13, 2017: 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
#2
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
#3
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
#4
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...
August 30, 2017: Journal of Thoracic and Cardiovascular Surgery
https://www.readbyqxmd.com/read/28903866/a-bayesian-latent-class-model-to-estimate-the-accuracy-of-pregnancy-diagnosis-by-transrectal-ultrasonography-and-laboratory-detection-of-pregnancy-associated-glycoproteins-in-dairy-cows
#5
G T Fosgate, B Motimele, A Ganswindt, P C Irons
Accurate diagnosis of pregnancy is an essential component of an effective reproductive management plan for dairy cattle. Indirect methods of pregnancy detection can be performed soon after breeding and offer an advantage over traditional direct methods in not requiring an experienced veterinarian and having potential for automation. The objective of this study was to estimate the sensitivity and specificity of pregnancy-associated glycoprotein (PAG) detection ELISA and transrectal ultrasound (TRUS) in dairy cows of South Africa using a Bayesian latent class approach...
September 15, 2017: Preventive Veterinary Medicine
https://www.readbyqxmd.com/read/28844720/development-and-standardization-of-an-in-house-indirect-elisa-for-detection-of-duck-antibody-to-fowl-cholera
#6
Pichayanut Poolperm, Thanya Varinrak, Yasushi Kataoka, Khajornsak Tragoolpua, Takuo Sawada, Nattawooti Sthitmatee
Serological tests, such as agglutination and indirect hemagglutination assay (IHA), have been used to identify antibodies against Pasteurella multocida in poultry sera, but none are highly sensitive. An enzyme-linked immunosorbent assays (ELISA) has been used with varying degrees of success in attempts to monitor seroconversion in vaccinated poultry, but are not suitable for diagnosis. Commercial ELISA kits are available for chickens and turkeys, but not for ducks. The present study reports development and standardization of an in-house indirect ELISA for detection of duck antibody to fowl cholera...
November 2017: Journal of Microbiological Methods
https://www.readbyqxmd.com/read/28752323/bone-tumor-diagnosis-using-a-na%C3%A3-ve-bayesian-model-of-demographic-and-radiographic-features
#7
Bao H Do, Curtis Langlotz, Christopher F Beaulieu
Because many bone tumors have a variety of appearances and are uncommon, few radiologists develop sufficient expertise to guide optimal management. Bayesian inference can guide decision-making by computing probabilities of multiple diagnoses to generate a differential. We built and validated a naïve Bayes machine (NBM) that processes 18 demographic and radiographic features. We reviewed over 1664 analog radiographic cases of bone tumors and selected 811 cases (66 diagnoses) for annotation using a quantitative imaging platform...
July 27, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28690054/fuzzy-evidential-network-and-its-application-as-medical-prognosis-and-diagnosis-models
#8
Amin Janghorbani, Mohammad Hassan Moradi
Uncertainty is one of the important facts of the medical knowledge. Medical prognosis and diagnosis, as the essential parts of medical knowledge, is affected by different aspects of uncertainty, which must be managed. In the previous studies, different theories such as Bayesian probability theory, evidence theory, and fuzzy set theory have been developed to represent and manage different aspects of uncertainty. Recently, hybrid frameworks are suggested to deal with various types of uncertainty in a single framework...
July 6, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28408880/a-bayesian-model-for-the-prediction-and-early-diagnosis-of-alzheimer-s-disease
#9
Athanasios Alexiou, Vasileios D Mantzavinos, Nigel H Greig, Mohammad A Kamal
Alzheimer's disease treatment is still an open problem. The diversity of symptoms, the alterations in common pathophysiology, the existence of asymptomatic cases, the different types of sporadic and familial Alzheimer's and their relevance with other types of dementia and comorbidities, have already created a myth-fear against the leading disease of the twenty first century. Many failed latest clinical trials and novel medications have revealed the early diagnosis as the most critical treatment solution, even though scientists tested the amyloid hypothesis and few related drugs...
2017: Frontiers in Aging Neuroscience
https://www.readbyqxmd.com/read/28397168/can-a-bayesian-belief-network-be-used-to-estimate-1-year-survival-in-patients-with-bone-sarcomas
#10
Rajpal Nandra, Michael Parry, Jonathan Forsberg, Robert Grimer
BACKGROUND: Extremity sarcoma has a preponderance to present late with advanced stage at diagnosis. It is important to know why these patients die early from sarcoma and to predict those at high risk. Currently we have mid- to long-term outcome data on which to counsel patients and support treatment decisions, but in contrast to other cancer groups, very little on short-term mortality. Bayesian belief network modeling has been used to develop decision-support tools in various oncologic diagnoses, but to our knowledge, this approach has not been applied to patients with extremity sarcoma...
June 2017: Clinical Orthopaedics and related Research
https://www.readbyqxmd.com/read/28384010/placebo-response-in-pediatric-anxiety-disorders-results-from-the-child-adolescent-anxiety-multimodal-study
#11
Jeffrey R Strawn, Eric T Dobson, Jeffrey A Mills, Gary J Cornwall, Dara Sakolsky, Boris Birmaher, Scott N Compton, John Piacentini, James T McCracken, Golda S Ginsburg, Phillip C Kendall, John T Walkup, Anne Marie Albano, Moira A Rynn
OBJECTIVES: The aim of this study is to identify predictors of pill placebo response and to characterize the temporal course of pill placebo response in anxious youth. METHODS: Data from placebo-treated patients (N = 76) in the Child/Adolescent Anxiety Multimodal Study (CAMS), a multisite, randomized controlled trial that examined the efficacy of cognitive-behavioral therapy, sertraline, their combination, and placebo for the treatment of separation, generalized, and social anxiety disorders, were evaluated...
August 2017: Journal of Child and Adolescent Psychopharmacology
https://www.readbyqxmd.com/read/28279374/the-quantitative-science-of-evaluating%C3%A2-imaging-evidence
#12
REVIEW
Tessa S S Genders, Bart S Ferket, M G Myriam Hunink
Cardiovascular diagnostic imaging tests are increasingly used in everyday clinical practice, but are often imperfect, just like any other diagnostic test. The performance of a cardiovascular diagnostic imaging test is usually expressed in terms of sensitivity and specificity compared with the reference standard (gold standard) for diagnosing the disease. However, evidence-based application of a diagnostic test also requires knowledge about the pre-test probability of disease, the benefit of making a correct diagnosis, the harm caused by false-positive imaging test results, and potential adverse effects of performing the test itself...
March 2017: JACC. Cardiovascular Imaging
https://www.readbyqxmd.com/read/28236025/incremental-diagnostic-quality-gain-of-cta-over-v-q-scan-in-the-assessment-of-pulmonary-embolism-by-means-of-a-wells-score-bayesian-model-results-from-the-acdc-collaboration
#13
Laila Cochon, Kaitlin McIntyre, José M Nicolás, Amado Alejandro Baez
OBJECTIVE: Our objective was to evaluate the diagnostic value of computed tomography angiography (CTA) and ventilation perfusion (V/Q) scan in the assessment of pulmonary embolism (PE) by means of a Bayesian statistical model. METHODS: Wells criteria defined pretest probability. Sensitivity and specificity of CTA and V/Q scan for PE were derived from pooled meta-analysis data. Likelihood ratios calculated for CTA and V/Q were inserted in the nomogram. Absolute (ADG) and relative diagnostic gains (RDG) were analyzed comparing post- and pretest probability...
August 2017: Emergency Radiology
https://www.readbyqxmd.com/read/28049518/an-ontological-analysis-of-medical-bayesian-indicators-of-performance
#14
Adrien Barton, Jean-François Ethier, Régis Duvauferrier, Anita Burgun
BACKGROUND: Biomedical ontologies aim at providing the most exhaustive and rigorous representation of reality as described by biomedical sciences. A large part of medical reasoning deals with diagnosis and is essentially probabilistic. It would be an asset for biomedical ontologies to be able to support such a probabilistic reasoning and formalize Bayesian indicators of performance: sensitivity, specificity, positive predictive value and negative predictive value. In doing so, one has to consider that not only the positive and negative predictive values, but also sensitivity and specificity depend upon the group under consideration: this is the "spectrum effect"...
January 3, 2017: Journal of Biomedical Semantics
https://www.readbyqxmd.com/read/28045023/meta-analytic-bayesian-model-for-differentiating-intestinal-tuberculosis-from-crohn-s-disease
#15
REVIEW
Julajak Limsrivilai, Andrew B Shreiner, Ananya Pongpaibul, Charlie Laohapand, Rewat Boonanuwat, Nonthalee Pausawasdi, Supot Pongprasobchai, Sathaporn Manatsathit, Peter D R Higgins
OBJECTIVES: Distinguishing intestinal tuberculosis (ITB) from Crohn's disease (CD) is difficult, although studies have reported clinical, endoscopic, imaging, and laboratory findings that help to differentiate these two diseases. We aimed to produce estimates of the predictive power of these findings and construct a comprehensive model to predict the probability of ITB vs. CD. METHODS: A systematic literature search for studies differentiating ITB from CD was conducted in MEDLINE, PUBMED, and EMBASE from inception until September 2015...
March 2017: American Journal of Gastroenterology
https://www.readbyqxmd.com/read/27913438/quantifying-the-dynamics-of-field-cancerization-in-tobacco-related-head-and-neck-cancer-a-multiscale-modeling-approach
#16
Marc D Ryser, Walter T Lee, Neal E Ready, Kevin Z Leder, Jasmine Foo
High rates of local recurrence in tobacco-related head and neck squamous cell carcinoma (HNSCC) are commonly attributed to unresected fields of precancerous tissue. Because they are not easily detectable at the time of surgery without additional biopsies, there is a need for noninvasive methods to predict the extent and dynamics of these fields. Here, we developed a spatial stochastic model of tobacco-related HNSCC at the tissue level and calibrated the model using a Bayesian framework and population-level incidence data from the Surveillance, Epidemiology, and End Results (SEER) registry...
December 15, 2016: Cancer Research
https://www.readbyqxmd.com/read/27885441/bayesian-comparative-assessment-of-diagnostic-accuracy-of-low-dose-ct-scan-and-ultrasonography-in-the-diagnosis-of-urolithiasis-after-the-application-of-the-stone-score
#17
Laila Cochon, Jeffrey Smith, Amado Alejandro Baez
OBJECTIVE: The objective of our study was to assess the diagnostic quality of low-dose computed tomography (CT) when compared to ultrasound (US) in diagnosis of urolithiasis using STONE score as a predictor of pre-test probability and the Bayesian statistical model to calculate post-test probabilities (POST) for both diagnostic tests. METHODS: STONE score was used to form risk groups to obtain pre-test probabilities. Likelihood ratios (LR) were calculated from external data for low-dose CT and US...
April 2017: Emergency Radiology
https://www.readbyqxmd.com/read/27818878/intelligent-framework-for-diagnosis-of-frozen-shoulder-using-cross-sectional-survey-and-case-studies
#18
Humaira Batool, M Usman Akram, Fouzia Batool, Wasi Haider Butt
OBJECTIVES: Frozen shoulder is a disease in which shoulder becomes stiff. Accurate diagnosis of frozen shoulder is helpful in providing economical and effective treatment for patients. This research provides the classification of unstructured data using data mining techniques. Prediction results are validated by K-fold cross-validation method. It also provides accurate diagnosis of frozen shoulder using Naïve Bayesian and Random Forest models. At the end results are presented by performance measure techniques...
2016: SpringerPlus
https://www.readbyqxmd.com/read/27752962/physician-bayesian-updating-from-personal-beliefs-about-the-base-rate-and-likelihood-ratio
#19
Benjamin Margolin Rottman
Whether humans can accurately make decisions in line with Bayes' rule has been one of the most important yet contentious topics in cognitive psychology. Though a number of paradigms have been used for studying Bayesian updating, rarely have subjects been allowed to use their own preexisting beliefs about the prior and the likelihood. A study is reported in which physicians judged the posttest probability of a diagnosis for a patient vignette after receiving a test result, and the physicians' posttest judgments were compared to the normative posttest calculated from their own beliefs in the sensitivity and false positive rate of the test (likelihood ratio) and prior probability of the diagnosis...
February 2017: Memory & Cognition
https://www.readbyqxmd.com/read/27722873/bayesian-pretest-probability-estimation-for-primary-malignant-bone-tumors-based-on-the-surveillance-epidemiology-and-end-results-program-seer-database
#20
Matthias Benndorf, Jakob Neubauer, Mathias Langer, Elmar Kotter
PURPOSE: In the diagnostic process of primary bone tumors, patient age, tumor localization and to a lesser extent sex affect the differential diagnosis. We therefore aim to develop a pretest probability calculator for primary malignant bone tumors based on population data taking these variables into account. METHODS: We access the SEER (Surveillance, Epidemiology and End Results Program of the National Cancer Institute, 2015 release) database and analyze data of all primary malignant bone tumors diagnosed between 1973 and 2012...
March 2017: International Journal of Computer Assisted Radiology and Surgery
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