Improving the accuracy of medical diagnosis with causal machine learning
Nature Communications, 2020 In medical diagnosis a doctor aims to explain a patient’s symptoms by determining the diseases causing them, while existing diagnostic algorithms are purely associative.
Jonathan G. Richens +2 more
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Improving statistical inference on pathogen densities estimated by quantitative molecular methods: malaria gametocytaemia as a case study [PDF]
, 2015 BACKGROUND: Quantitative molecular methods (QMMs) such as quantitative real-time polymerase chain reaction (q-PCR), reverse-transcriptase PCR (qRT-PCR) and quantitative nucleic acid sequence-based amplification (QT-NASBA) are increasingly used to ...
A Gelman +56 more
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Neuro-fuzzy knowledge processing in intelligent learning environments for improved student diagnosis [PDF]
, 2005 In this paper, a neural network implementation for a fuzzy logic-based model of the diagnostic process is proposed as a means to achieve accurate student diagnosis and updates of the student model in Intelligent Learning Environments.
Grigoriadou, M. +3 more
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Statistical Methods for Targeted Clinical Trials under Enrichment Design
Journal of the Formosan Medical Association, 2008 After completion of the Human Genome Project, disease targets at the molecular level can be identified. Treatment for these specific targets can be developed with the individualized treatment of patients becoming a reality.
Jen-Pei Liu, Jr-Rung Lin
doaj +1 more source
Local sensitivity diagnostics for Bayesian inference [PDF]
The Annals of Statistics, 1995 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gustafson, Paul, Wasserman, Larry
openaire +2 more sources
Journal of Medical Internet Research, 2020 BackgroundAssigning meaningful probabilities of SARS-CoV-2 infection risk presents a diagnostic challenge across the continuum of care. ObjectiveThe aim of this study was to develop and clinically validate an adaptable, personalized ...
D'Ambrosia, Christopher +2 more
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Variational Bayes inference for hidden Markov diagnostic classification models
British Journal of Mathematical and Statistical Psychology, 2021 Abstract Diagnostic classification models (DCMs) can be used to track the cognitive learning states of students across multiple time points or over repeated measurements. This study developed an effective variational Bayes (VB) inference method for hidden Markov longitudinal general DCMs.
Kazuhiro Yamaguchi, Alfonso J. Martinez
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Evidence cross-validation and Bayesian inference of MAST plasma equilibria [PDF]
, 2015 In this paper, current profiles for plasma discharges on the Mega-Ampere Spherical Tokamak (MAST) are directly calculated from pickup coil, flux loop and Motional-Stark Effect (MSE) observations via methods based in the statistical theory of Bayesian ...
Appel, L. +3 more
core +1 more source
Visual aids improve diagnostic inferences and metacognitive judgment calibration [PDF]
Frontiers in Psychology, 2015 Visual aids can improve comprehension of risks associated with medical treatments, screenings, and lifestyles. Do visual aids also help decision makers accurately assess their risk comprehension? That is, do visual aids help them become well calibrated?
Rocio eGarcia-Retamero +5 more
openaire +6 more sources
Aided diagnosis of structural pathologies with an expert system [PDF]
, 2013 Sustainability and safety are social demands for long-life buildings. Suitable inspection and maintenance tasks on structural elements are needed for keeping buildings safely in service.
Bernat Masó, Ernest, Gil Espert, Lluís
core +2 more sources