AI Medical Compendium Topic:
Models, Statistical

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Interpretable Probabilistic Latent Variable Models for Automatic Annotation of Clinical Text.

AMIA ... Annual Symposium proceedings. AMIA Symposium
We propose Latent Class Allocation (LCA) and Discriminative Labeled Latent Dirichlet Allocation (DL-LDA), two novel interpretable probabilistic latent variable models for automatic annotation of clinical text. Both models separate the terms that are ...

Forecasting Natural Gas Prices Using Wavelets, Time Series, and Artificial Neural Networks.

PloS one
Following the unconventional gas revolution, the forecasting of natural gas prices has become increasingly important because the association of these prices with those of crude oil has weakened. With this as motivation, we propose some modified hybri...

A Bayesian Developmental Approach to Robotic Goal-Based Imitation Learning.

PloS one
A fundamental challenge in robotics today is building robots that can learn new skills by observing humans and imitating human actions. We propose a new Bayesian approach to robotic learning by imitation inspired by the developmental hypothesis that ...

Outcome Prediction in Clinical Treatment Processes.

Journal of medical systems
Clinical outcome prediction, as strong implications for health service delivery of clinical treatment processes (CTPs), is important for both patients and healthcare providers. Prior studies typically use a priori knowledge, such as demographics or p...

Robust fixed-time synchronization of delayed Cohen-Grossberg neural networks.

Neural networks : the official journal of the International Neural Network Society
The fixed-time master-slave synchronization of Cohen-Grossberg neural networks with parameter uncertainties and time-varying delays is investigated. Compared with finite-time synchronization where the convergence time relies on the initial synchroniz...

One pass learning for generalized classifier neural network.

Neural networks : the official journal of the International Neural Network Society
Generalized classifier neural network introduced as a kind of radial basis function neural network, uses gradient descent based optimized smoothing parameter value to provide efficient classification. However, optimization consumes quite a long time ...

Global O(t(-α)) stability and global asymptotical periodicity for a non-autonomous fractional-order neural networks with time-varying delays.

Neural networks : the official journal of the International Neural Network Society
The present paper studies global O(t(-α)) stability and global asymptotical periodicity for a non-autonomous fractional-order neural networks with time-varying delays (FDNN). Firstly, some sufficient conditions are established to ensure that a non-au...

Extracting motor synergies from random movements for low-dimensional task-space control of musculoskeletal robots.

Bioinspiration & biomimetics
In the field of human motor control, the motor synergy hypothesis explains how humans simplify body control dimensionality by coordinating groups of muscles, called motor synergies, instead of controlling muscles independently. In most applications o...

Imparting protean behavior to mobile robots accomplishing patrolling tasks in the presence of adversaries.

Bioinspiration & biomimetics
Providing unpredictable trajectories for patrol robots is essential when coping with adversaries. In order to solve this problem we developed an effective approach based on the known protean behavior of individual prey animals-random zig-zag movement...

Using Wearable Sensors and Machine Learning Models to Separate Functional Upper Extremity Use From Walking-Associated Arm Movements.

Archives of physical medicine and rehabilitation
OBJECTIVE: To improve measurement of upper extremity (UE) use in the community by evaluating the feasibility of using body-worn sensor data and machine learning models to distinguish productive prehensile and bimanual UE activity use from extraneous ...