AIMC Topic: Bayes Theorem

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Comparison of Machine Learning Models for the Androgen Receptor.

Environmental science & technology Oct 21, 2020
The androgen receptor (AR) is a target of interest for endocrine disruption research, as altered signaling can affect normal reproductive and neurological development for generations. In an effort to prioritize compounds with alternative methodologie...
Receptors, Androgen United States Androgens Bayes Theorem Machine Learning Prospective Studies
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Machine learning techniques for mortality prediction in critical traumatic patients: anatomic and physiologic variables from the RETRAUCI study.

BMC medical research methodology Oct 20, 2020
BACKGROUND: Interest in models for calculating the risk of death in traumatic patients admitted to ICUs remains high. These models use variables derived from the deviation of physiological parameters and/or the severity of anatomical lesions with res...
Bayes Theorem Algorithms Logistic Models Machine Learning Humans Neural Networks, Computer
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Predicting the consequences of accidents involving dangerous substances using machine learning.

Ecotoxicology and environmental safety Oct 19, 2020
A new dimension of learning lessons from the occurrence of hazardous events involving dangerous substances is considered relying on the availability of representative data and the significant evolution of a wide range of machine learning tools. The i...
Support Vector Machine Bayes Theorem Accidents Neural Networks, Computer Chemical Hazard Release Machine Learning Forecasting Algorithms Humans Logistic Models
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Detecting Technical Anomalies in High-Frequency Water-Quality Data Using Artificial Neural Networks.

Environmental science & technology Oct 16, 2020
Anomaly detection (AD) in high-volume environmental data requires one to tackle a series of challenges associated with the typical low frequency of anomalous events, the broad-range of possible anomaly types, and local nonstationary environmental con...
Bayes Theorem Water Quality Neural Networks, Computer Water
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Artificial Intelligence (AI) to the Rescue: Deploying Machine Learning to Bridge the Biorelevance Gap in Antioxidant Assays.

SLAS technology Oct 15, 2020
Oxidative stress induced by excessive levels of reactive oxygen species (ROS) underlies several diseases. Therapeutic strategies to combat oxidative damage are, therefore, a subject of intense scientific investigation to prevent and treat such diseas...
Artificial Intelligence Antioxidants Bayes Theorem Machine Learning Animals F2-Isoprostanes
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OCT Signal Enhancement with Deep Learning.

Ophthalmology. Glaucoma Oct 15, 2020
PURPOSE: To establish whether deep learning methods are able to improve the signal-to-noise ratio of time-domain (TD) OCT images to approach that of spectral-domain (SD) OCT images.
Glaucoma, Open-Angle Double-Blind Method Bayes Theorem Humans Deep Learning Tomography, Optical Coherence
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Artificial Intelligence Algorithms to Diagnose Glaucoma and Detect Glaucoma Progression: Translation to Clinical Practice.

Translational vision science & technology Oct 15, 2020
PURPOSE: This concise review aims to explore the potential for the clinical implementation of artificial intelligence (AI) strategies for detecting glaucoma and monitoring glaucoma progression.
Algorithms Humans Bayes Theorem Visual Field Tests Glaucoma Artificial Intelligence
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Bayesian Algorithm for Retrosynthesis.

Journal of chemical information and modeling Oct 13, 2020
The identification of synthetic routes that end with the desired product is considered an inherently time-consuming process that is largely dependent on expert knowledge regarding a limited proportion of the entire reaction space. At present, emergin...
Bayes Theorem Monte Carlo Method Machine Learning Neural Networks, Computer Algorithms
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Automated cephalometric landmark detection with confidence regions using Bayesian convolutional neural networks.

BMC oral health Oct 7, 2020
BACKGROUND: Despite the integral role of cephalometric analysis in orthodontics, there have been limitations regarding the reliability, accuracy, etc. of cephalometric landmarks tracing. Attempts on developing automatic plotting systems have continuo...
Bayes Theorem Reproducibility of Results Anatomic Landmarks Image Processing, Computer-Assisted Cephalometry Neural Networks, Computer
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IAMPE: NMR-Assisted Computational Prediction of Antimicrobial Peptides.

Journal of chemical information and modeling Sep 30, 2020
Antimicrobial peptides (AMPs) are at the focus of attention due to their therapeutic importance and developing computational tools for the identification of efficient antibiotics from the primary structure. Here, we utilized the CNMR spectral of amin...
Bayes Theorem Pore Forming Cytotoxic Proteins Computational Biology Algorithms Amino Acids Support Vector Machine
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