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Predicción de mortalidad en recién nacidos prematuros. Revisión sistemática actualizada
Anales de Pediatría, 2020 Resumen: Introducción: La prematuridad extrema se asocia a altas tasas de mortalidad. Para profesionales y familias, es prioritario establecer de forma individualizada las probabilidades de muerte en diferentes momentos.
Ruth del Río +4 more
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EBioMedicine, 2021 Background: Acute lymphoblastic leukaemia with mixed lineage leukaemia gene rearrangement (MLL-ALL) frequently affects infants and is associated with a poor prognosis.
Anne P. de Groot +20 more
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Clinical prediction models [PDF]
British Journal of Surgery, 2016 Clinical prediction models (also known as prognostic models, risk scores) are mathematical equations that relate multiple predictors (risk factors, co-variates) to the probability of having a disease or condition (diagnostic) or the probability that an event will happen in the future (prognostic).
Ranstam, J, Cook, J, Collins, G
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Better null models for assessing predictive accuracy of disease models.
PLoS ONE, 2023 Null models provide a critical baseline for the evaluation of predictive disease models. Many studies consider only the grand mean null model (i.e. R2) when evaluating the predictive ability of a model, which is insufficient to convey the predictive ...
Alexander C Keyel, A Marm Kilpatrick
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Prediction models in urology [PDF]
Nature Clinical Practice Urology, 2007 Predicting risk is an inherent feature of clinical practice. How likely is a man with a given PSA level to have prostate cancer? Can lymph node dissection be safely avoided in a patient with testicular cancer? Should chemotherapy be given after cystectomy for bladder cancer?
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Modelling: Predictive yield [PDF]
Nature, 2013 Farmers would benefit from better long-range weather forecasts. What else can science provide to help them decide what to plant?
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Modeling program predictability [PDF]
ACM SIGARCH Computer Architecture News, 1998 Basic properties of program predictability --- for both values and control --- are defined and studied. We take the view that program predictability originates at certain points during a program's execution, flows through subsequent instructions, and then ends at other points in the program. These key components of predictability:
Yiannakis Sazeides, James E. Smith 0001
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Prediction Algorithm for State Prediction Model
Journal of Computers, 2012 Dynamic Bayesian network is the extension of Bayesian network in solving time series problems .It can be well dealt with the time-varying multivariable problem. A state model is given based on Dynamic Bayesian network. The model can more accurately describe the relationship between the system state and the influencing factors.
Zili Zhang +3 more
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A predictive coding model of the N400 [PDF]
Cognition, 2023 Abstract The N400 event-related component has been widely used to investigate the neural mechanisms underlying real-time language comprehension. However, despite decades of research, there is still no unifying theory that can explain both its temporal dynamics and functional properties.
Samer Nour Eddine +4 more
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Clinical and Translational Gastroenterology, 2014 Prediction research is becoming increasing popular; however, the differences between traditional explanatory research and prediction research are often poorly understood, resulting in a wide variation in the methodologic quality of prediction research.
Waljee, Akbar K +2 more
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