AI Medical Compendium Topic:
Models, Theoretical

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A hybrid deep learning framework for bacterial named entity recognition with domain features.

BMC bioinformatics
BACKGROUND: Microbes have been shown to play a crucial role in various ecosystems. Many human diseases have been proved to be associated with bacteria, so it is essential to extract the interaction between bacteria for medical research and applicatio...

Integrating functional connectivity and MVPA through a multiple constraint network analysis.

NeuroImage
Traditional general linear model-based brain mapping efforts using functional neuroimaging are complemented by more recent multivariate pattern analyses (MVPA) that apply machine learning techniques to identify the cognitive states associated with re...

Standard operating procedure for curation and clinical interpretation of variants in cancer.

Genome medicine
Manually curated variant knowledgebases and their associated knowledge models are serving an increasingly important role in distributing and interpreting variants in cancer. These knowledgebases vary in their level of public accessibility, and the co...

Latent Dirichlet Allocation in predicting clinical trial terminations.

BMC medical informatics and decision making
BACKGROUND: This study used natural language processing (NLP) and machine learning (ML) techniques to identify reliable patterns from within research narrative documents to distinguish studies that complete successfully, from the ones that terminate....

Evaluating a Semiautonomous Brain-Computer Interface Based on Conformal Geometric Algebra and Artificial Vision.

Computational intelligence and neuroscience
In this paper, we evaluate a semiautonomous brain-computer interface (BCI) for manipulation tasks. In such a system, the user controls a robotic arm through motor imagery commands. In traditional process-control BCI systems, the user has to provide t...

Improved Transductive Support Vector Machine for a Small Labelled Set in Motor Imagery-Based Brain-Computer Interface.

Computational intelligence and neuroscience
Long and tedious calibration time hinders the development of motor imagery- (MI-) based brain-computer interface (BCI). To tackle this problem, we use a limited labelled set and a relatively large unlabelled set from the same subject for training bas...

Reprint of: Analysis of an evolutionary algorithm for complex fuzzy cognitive map learning based on graph theory metrics and output concepts.

Bio Systems
The fuzzy cognitive map (FCM) is an effective tool for modeling dynamic decision support systems. It describes the analyzed phenomenon in the form of key concepts and the causal connections between them. The main aspects of the building of the FCM mo...

Adaptive Fusion-Based Autonomous Laparoscope Control for Semi-Autonomous Surgery.

Journal of medical systems
The purpose of this paper is to develop an autonomous tracking algorithm based on adaptive fusion kinematics method, the autonomous laparoscope control algorithm and adaptive fusion kinematics method are proposed for semi-autonomous surgery, focus on...

Artificial intelligence based approaches to evaluate actual evapotranspiration in wetlands.

The Science of the total environment
Wetlands are extraordinary ecosystems and important climate regulators that also contribute to reduce natural disaster risk. Unfortunately, wetlands are declining much faster than forests. The safeguarding of the wetlands also needs knowledge of the ...

Deep learning modeling using normal mammograms for predicting breast cancer risk.

Medical physics
PURPOSE: To investigate two deep learning-based modeling schemes for predicting short-term risk of developing breast cancer using prior normal screening digital mammograms in a case-control setting.