AIMC Topic: Bayes Theorem
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PTML Model of ChEMBL Compounds Assays for Vitamin Derivatives.
ACS combinatorial science
Feb 13, 2020
Determining the biological activity of vitamin derivatives is needed given that organic synthesis of analogs of vitamins is an active field of interest for medicinal chemistry, pharmaceuticals, and food additives. Accordingly, scientists from differe...
Comparison of Two Bayesian-MCMC Inversion Methods for Laboratory Infiltration and Field Irrigation Experiments.
International journal of environmental research and public health
Feb 10, 2020
Bayesian parameter inversion approaches are dependent on the original forward models linking subsurface physical properties to measured data, which usually require a large number of iterations. Fast alternative systems to forward models are commonly ...
Improving genomic prediction accuracy for meat tenderness in Nellore cattle using artificial neural networks.
Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie
Feb 5, 2020
The goal of this study was to compare the predictive performance of artificial neural networks (ANNs) with Bayesian ridge regression, Bayesian Lasso, Bayes A, Bayes B and Bayes Cπ in estimating genomic breeding values for meat tenderness in Nellore c...
Generalized Pharmacometric Modeling, a Novel Paradigm for Integrating Machine Learning Algorithms: A Case Study of Metabolomic Biomarkers.
Clinical pharmacology and therapeutics
Jan 28, 2020
There is an unmet need for identifying innovative machine learning (ML) strategies to improve drug treatment regimens and therapeutic outcomes. We investigate Generalized Pharmacometric Modeling (GPM), a novel paradigm that integrates ML algorithms w...
Big Data Analytics and Sensor-Enhanced Activity Management to Improve Effectiveness and Efficiency of Outpatient Medical Rehabilitation.
International journal of environmental research and public health
Jan 24, 2020
Numerous societal trends are compelling a transition from inpatient to outpatient venues of care for medical rehabilitation. While there are advantages to outpatient rehabilitation (e.g., lower cost, more relevant to home and community function), the...
Benchmarking Deep Learning Architectures for Predicting Readmission to the ICU and Describing Patients-at-Risk.
Scientific reports
Jan 24, 2020
To compare different deep learning architectures for predicting the risk of readmission within 30 days of discharge from the intensive care unit (ICU). The interpretability of attention-based models is leveraged to describe patients-at-risk. Several ...
Investigating the use of data-driven artificial intelligence in computerised decision support systems for health and social care: A systematic review.
Health informatics journal
Jan 22, 2020
There is growing interest in the potential of artificial intelligence to support decision-making in health and social care settings. There is, however, currently limited evidence of the effectiveness of these systems. The aim of this study was to inv...
Application of data mining in a cohort of Italian subjects undergoing myocardial perfusion imaging at an academic medical center.
Computer methods and programs in biomedicine
Jan 16, 2020
INTRODUCTION: Coronary artery disease (CAD) is still one of the primary causes of death in the developed countries. Stress single-photon emission computed tomography is used to evaluate myocardial perfusion and ventricular function in patients with s...
Dynamic coronary roadmapping via catheter tip tracking in X-ray fluoroscopy with deep learning based Bayesian filtering.
Medical image analysis
Jan 11, 2020
Percutaneous coronary intervention (PCI) is typically performed with image guidance using X-ray angiograms in which coronary arteries are opacified with X-ray opaque contrast agents. Interventional cardiologists typically navigate instruments using n...
Polygenic risk scores outperform machine learning methods in predicting coronary artery disease status.
Genetic epidemiology
Jan 10, 2020
Coronary artery disease (CAD) is the leading global cause of mortality and has substantial heritability with a polygenic architecture. Recent approaches of risk prediction were based on polygenic risk scores (PRS) not taking possible nonlinear effect...
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