AIMC Topic: Informatics

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Public Health and Epidemiology Informatics: Can Artificial Intelligence Help Future Global Challenges? An Overview of Antimicrobial Resistance and Impact of Climate Change in Disease Epidemiology.

Yearbook of medical informatics Aug 16, 2019
OBJECTIVES: To provide an oveiview of the current application of artificial intelligence (AI) in the field of public health and epidemiology, with a special focus on antimicrobial resistance and the impact of climate change in disease epidemiology. B...
Humans Artificial Intelligence Anti-Bacterial Agents Climate Change Informatics Epidemiology Drug Resistance, Bacterial Public Health
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Evaluation of Cross-Validation Strategies in Sequence-Based Binding Prediction Using Deep Learning.

Journal of chemical information and modeling Feb 22, 2019
Binding prediction between targets and drug-like compounds through deep neural networks has generated promising results in recent years, outperforming traditional machine learning-based methods. However, the generalization capability of these classif...
Quantitative Structure-Activity Relationship Informatics Drug Discovery Deep Learning Reproducibility of Results
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Converging a Knowledge-Based Scoring Function: DrugScore.

Journal of chemical information and modeling Dec 18, 2018
We present DrugScore, a new version of the knowledge-based scoring function DrugScore, which builds upon the same formalism used to derive DrugScore but exploits a training data set of nearly 40 000 X-ray complex structures, a highly diverse and the,...
Ligands Informatics Models, Molecular Knowledge Bases Drug Design
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A Survey of Multi-task Learning Methods in Chemoinformatics.

Molecular informatics Nov 28, 2018
Despite the increasing volume of available data, the proportion of experimentally measured data remains small compared to the virtual chemical space of possible chemical structures. Therefore, there is a strong interest in simultaneously predicting d...
Machine Learning Databases, Chemical Informatics Chemistry
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A New Approach for Advertising CTR Prediction Based on Deep Neural Network via Attention Mechanism.

Computational and mathematical methods in medicine Sep 13, 2018
Click-through rate prediction is critical in Internet advertising and affects web publisher's profits and advertiser's payment. The traditional method of obtaining features using feature extraction did not consider the sparseness of advertising data ...
Machine Learning Algorithms Reproducibility of Results Humans Informatics Neural Networks, Computer Internet Models, Statistical Advertising Attention Area Under Curve
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Reliable and Performant Identification of Low-Energy Conformers in the Gas Phase and Water.

Journal of chemical information and modeling May 16, 2018
Prediction of compound properties from structure via quantitative structure-activity relationship and machine-learning approaches is an important computational chemistry task in small-molecule drug research. Though many such properties are dependent ...
Thermodynamics Solvents Molecular Conformation Gases Informatics Quantitative Structure-Activity Relationship Models, Molecular Pharmaceutical Preparations Drug Discovery Water Machine Learning
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Conformal Regression for Quantitative Structure-Activity Relationship Modeling-Quantifying Prediction Uncertainty.

Journal of chemical information and modeling May 10, 2018
Making predictions with an associated confidence is highly desirable as it facilitates decision making and resource prioritization. Conformal regression is a machine learning framework that allows the user to define the required confidence and delive...
Decision Making Quantitative Structure-Activity Relationship Machine Learning Informatics Uncertainty
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Machine learning in chemoinformatics and drug discovery.

Drug discovery today May 8, 2018
Chemoinformatics is an established discipline focusing on extracting, processing and extrapolating meaningful data from chemical structures. With the rapid explosion of chemical 'big' data from HTS and combinatorial synthesis, machine learning has be...
Machine Learning Animals Humans High-Throughput Screening Assays Pattern Recognition, Automated Informatics Pharmaceutical Preparations Drug Discovery Quantitative Structure-Activity Relationship Diffusion of Innovation Molecular Structure
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Deep Learning Based Regression and Multiclass Models for Acute Oral Toxicity Prediction with Automatic Chemical Feature Extraction.

Journal of chemical information and modeling Oct 27, 2017
Median lethal death, LD, is a general indicator of compound acute oral toxicity (AOT). Various in silico methods were developed for AOT prediction to reduce costs and time. In this study, we developed an improved molecular graph encoding convolutiona...
Machine Learning Automation Lethal Dose 50 Toxicity Tests Models, Statistical Informatics Regression Analysis Administration, Oral
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Shallow Representation Learning via Kernel PCA Improves QSAR Modelability.

Journal of chemical information and modeling Aug 7, 2017
Linear models offer a robust, flexible, and computationally efficient set of tools for modeling quantitative structure-activity relationships (QSARs) but have been eclipsed in performance by nonlinear methods. Support vector machines (SVMs) and neura...
Informatics Time Factors Principal Component Analysis Support Vector Machine Quantitative Structure-Activity Relationship
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