AIMC Topic:
Models, Theoretical

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Rapid identification of slow healing wounds.

Wound repair and regeneration : official publication of the Wound Healing Society [and] the European Tissue Repair Society
Chronic nonhealing wounds have a prevalence of 2% in the United States, and cost an estimated $50 billion annually. Accurate stratification of wounds for risk of slow healing may help guide treatment and referral decisions. We have applied modern mac...

Multi-source adaptation joint kernel sparse representation for visual classification.

Neural networks : the official journal of the International Neural Network Society
Most of the existing domain adaptation learning (DAL) methods relies on a single source domain to learn a classifier with well-generalized performance for the target domain of interest, which may lead to the so-called negative transfer problem. To th...

Computerized "Learn-As-You-Go" classification of traumatic brain injuries using NEISS narrative data.

Accident; analysis and prevention
One important routine task in injury research is to effectively classify injury circumstances into user-defined categories when using narrative text. However, traditional manual processes can be time consuming, and existing batch learning systems can...

Experimental Matching of Instances to Heuristics for Constraint Satisfaction Problems.

Computational intelligence and neuroscience
Constraint satisfaction problems are of special interest for the artificial intelligence and operations research community due to their many applications. Although heuristics involved in solving these problems have largely been studied in the past, l...

An ensemble of dynamic neural network identifiers for fault detection and isolation of gas turbine engines.

Neural networks : the official journal of the International Neural Network Society
In this paper, a new approach for Fault Detection and Isolation (FDI) of gas turbine engines is proposed by developing an ensemble of dynamic neural network identifiers. For health monitoring of the gas turbine engine, its dynamics is first identifie...

Exploring the Combination of Dempster-Shafer Theory and Neural Network for Predicting Trust and Distrust.

Computational intelligence and neuroscience
In social media, trust and distrust among users are important factors in helping users make decisions, dissect information, and receive recommendations. However, the sparsity and imbalance of social relations bring great difficulties and challenges i...

Development of Personalized Health Messages to Promote Engagement in Advance Care Planning.

Journal of the American Geriatrics Society
OBJECTIVES: To develop and test the acceptability of personalized intervention materials to promote advance care planning (ACP) based on the Transtheoretical Model (TTM), in which readiness to change is a critical organizing construct.

Analysis of the relation between health statistics and eating habits in Japanese prefectures using fuzzy robust regression model.

Computers in biology and medicine
In recent years, the Japanese Ministry of Health, Labour, and Welfare is working to improve citizen׳s lifestyle and social environment to improve their health. This is because of the following reasons. Diseases related to lifestyle such as malignant ...

Semantic representation of reported measurements in radiology.

BMC medical informatics and decision making
BACKGROUND: In radiology, a vast amount of diverse data is generated, and unstructured reporting is standard. Hence, much useful information is trapped in free-text form, and often lost in translation and transmission. One relevant source of free-tex...

Advanced Residuals Analysis for Determining the Number of PARAFAC Components in Dissolved Organic Matter.

Applied spectroscopy
Parallel factor analysis (PARAFAC) has facilitated an explosion in research connecting the fluorescence properties of dissolved organic matter (DOM) to its functions and biogeochemical cycling in natural and engineered systems. However, the validatio...