AIMC Topic: Linear Models
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Clinical text annotation - what factors are associated with the cost of time?
AMIA ... Annual Symposium proceedings. AMIA Symposium
Dec 5, 2018
Building high-quality annotated clinical corpora is necessary for developing statistical Natural Language Processing (NLP) models to unlock information embedded in clinical text, but it is also time consuming and expensive. Consequently, it important...
Gaussian Process Regression Models for the Prediction of Hydrogen Bond Acceptor Strengths.
Molecular informatics
Nov 25, 2018
We present two approaches for the computation of hydrogen bond acceptor strengths, one by machine-learning and one by a composite quantum-mechanical protocol, both based on the well-established pK scale and dataset. The QM calculations after a necess...
Machine Learning Methods as a Tool for Predicting Risk of Illness Applying Next-Generation Sequencing Data.
Risk analysis : an official publication of the Society for Risk Analysis
Nov 21, 2018
Next-generation sequencing (NGS) data present an untapped potential to improve microbial risk assessment (MRA) through increased specificity and redefinition of the hazard. Most of the MRA models do not account for differences in survivability and vi...
High waist-to-hip ratio levels are associated with insulin resistance markers in normal-weight women.
Diabetes & metabolic syndrome
Nov 14, 2018
AIM: To assess the association between high waist-to-hip ratio (WHR) levels and insulin resistance (IR) or hyperinsulinemia after oral glucose tolerance test (OGTT) in a sample of normal-weight women.
Multistability of Switched Neural Networks With Piecewise Linear Activation Functions Under State-Dependent Switching.
IEEE transactions on neural networks and learning systems
Nov 12, 2018
This paper is concerned with the multistability of switched neural networks with piecewise linear activation functions under state-dependent switching. Under some reasonable assumptions on the switching threshold and activation functions, by using th...
In Silico Prediction of O⁶-Methylguanine-DNA Methyltransferase Inhibitory Potency of Base Analogs with QSAR and Machine Learning Methods.
Molecules (Basel, Switzerland)
Nov 6, 2018
O⁶-methylguanine-DNA methyltransferase (MGMT), a unique DNA repair enzyme, can confer resistance to DNA anticancer alkylating agents that modify the O⁶-position of guanine. Thus, inhibition of MGMT activity in tumors has a great interest for cancer r...
A machine learning ensemble to predict treatment outcomes following an Internet intervention for depression.
Psychological medicine
Nov 5, 2018
BACKGROUND: Some Internet interventions are regarded as effective treatments for adult depression, but less is known about who responds to this form of treatment.
Semi-supervised machine learning approaches for predicting the chronology of archaeological sites: A case study of temples from medieval Angkor, Cambodia.
PloS one
Nov 5, 2018
Archaeologists often need to date and group artifact types to discern typologies, chronologies, and classifications. For over a century, statisticians have been using classification and clustering techniques to infer patterns in data that can be defi...
Rainfall time series disaggregation in mountainous regions using hybrid wavelet-artificial intelligence methods.
Environmental research
Oct 15, 2018
In mountainous regions, rainfall can be extremely variable in space and time. The need to simulate rainfall time series at different scales on one hand and the lack of recording such parameters in small scales because of administrative and economic p...
Urban population exposure to tropospheric ozone: A multi-country forecasting of SOMO35 using artificial neural networks.
Environmental pollution (Barking, Essex : 1987)
Oct 13, 2018
Urban population exposure to tropospheric ozone is a serious health concern in Europe countries. Although there are insufficient evidence to derive a level below which ozone has no effect on mortality WHO (World Health Organization) uses SOMO35 (sum ...
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