AIMC Topic: Data Interpretation, Statistical
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Machine learning in computational docking.
Artificial intelligence in medicine
Feb 16, 2015
OBJECTIVE: The objective of this paper is to highlight the state-of-the-art machine learning (ML) techniques in computational docking. The use of smart computational methods in the life cycle of drug design is relatively a recent development that has...
Improving propensity score estimators' robustness to model misspecification using super learner.
American journal of epidemiology
Dec 16, 2014
The consistency of propensity score (PS) estimators relies on correct specification of the PS model. The PS is frequently estimated using main-effects logistic regression. However, the underlying model assumptions may not hold. Machine learning metho...
Ensemble learning of inverse probability weights for marginal structural modeling in large observational datasets.
Statistics in medicine
Oct 15, 2014
Inverse probability weights used to fit marginal structural models are typically estimated using logistic regression. However, a data-adaptive procedure may be able to better exploit information available in measured covariates. By combining predicti...
Measuring quality of life with fuzzy numbers: in the perspectives of reliability, validity, measurement invariance, and feasibility.
Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation
Oct 14, 2014
PURPOSE: Fuzzy set theory (FST) can improve various aspects of measurement with questionnaires. However, very little is known about how to use FST to measure quality of life (QOL). The main purpose of our study was to find an appropriate fuzzy measur...
Accept/decline decision module for the liver simulated allocation model.
Health care management science
Aug 30, 2014
Simulated allocation models (SAMs) are used to evaluate organ allocation policies. An important component of SAMs is a module that decides whether each potential recipient will accept an offered organ. The objective of this study was to develop and t...
Kernel methods for large-scale genomic data analysis.
Briefings in bioinformatics
Jul 22, 2014
Machine learning, particularly kernel methods, has been demonstrated as a promising new tool to tackle the challenges imposed by today's explosive data growth in genomics. They provide a practical and principled approach to learning how a large numbe...
A data-driven approach to prostate cancer detection from dynamic contrast enhanced MRI.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jul 5, 2014
Magnetic resonance imaging (MRI), particularly dynamic contrast enhanced (DCE) imaging, has shown great potential in prostate cancer diagnosis and staging. In the current practice of DCE-MRI, diagnosis is based on quantitative parameters extracted fr...
Image Interpretation, Computer-Assisted
Pattern Recognition, Automated
Image Enhancement
Principal Component Analysis
Data Interpretation, Statistical
Prostatic Neoplasms
Reproducibility of Results
Aged
Sensitivity and Specificity
Male
Middle Aged
Humans
Magnetic Resonance Imaging
Multimodal Imaging
Machine Learning
Algorithms
Computer Simulation
PANDA-T1ρ: Integrating principal component analysis and dictionary learning for fast T1ρ mapping.
Magnetic resonance in medicine
Feb 14, 2014
PURPOSE: Long scanning time greatly hinders the widespread application of spin-lattice relaxation in rotating frame (T1ρ) in clinics. In this study, a novel method is proposed to reconstruct the T1ρ-weighted images from undersampled k-space data and ...
Algorithms
Humans
Subtraction Technique
Reproducibility of Results
Brain
Machine Learning
Sensitivity and Specificity
Computer Simulation
Magnetic Resonance Imaging
Spinal Cord
Principal Component Analysis
Models, Statistical
Pattern Recognition, Automated
Data Interpretation, Statistical
Image Enhancement
Image Interpretation, Computer-Assisted
Systems Integration
A multistaged automatic restoration of noisy microscopy cell images.
IEEE journal of biomedical and health informatics
Feb 10, 2014
Automated cell segmentation for microscopy cell images has recently become an initial step for further image analysis in cell biology. However, microscopy cell images are easily degraded by noise during the readout procedure via optical-electronic im...
Development of an Interpretable Machine Learning Model for Neurotoxicity Prediction of Environmentally Related Compounds.
Environmental science & technology
Jun 10, 2025
The rising prevalence of nervous system disorders has become a significant global health challenge, with environmental pollutants identified as key contributors. However, the large number of environmental related compounds, combined with the low effi...
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