AI Medical Compendium Topic:
Models, Theoretical

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Breast cancer data analysis for survivability studies and prediction.

Computer methods and programs in biomedicine
BACKGROUND: Breast cancer is the most common cancer affecting females worldwide. Breast cancer survivability prediction is challenging and a complex research task. Existing approaches engage statistical methods or supervised machine learning to asses...

An adaptive map-matching algorithm based on hierarchical fuzzy system from vehicular GPS data.

PloS one
An improved hierarchical fuzzy inference method based on C-measure map-matching algorithm is proposed in this paper, in which the C-measure represents the certainty or probability of the vehicle traveling on the actual road. A strategy is firstly int...

Impact of subclinical mastitis on greenhouse gas emissions intensity and profitability of dairy cows in Norway.

Preventive veterinary medicine
Impaired animal health causes both productivity and profitability losses on dairy farms, resulting in inefficient use of inputs and increase in greenhouse gas (GHG) emissions produced per unit of product (i.e. emissions intensity). Here, we used subc...

Classification of G-protein coupled receptors based on a rich generation of convolutional neural network, N-gram transformation and multiple sequence alignments.

Amino acids
Sequence classification is crucial in predicting the function of newly discovered sequences. In recent years, the prediction of the incremental large-scale and diversity of sequences has heavily relied on the involvement of machine-learning algorithm...

Forecasting carbon dioxide emissions based on a hybrid of mixed data sampling regression model and back propagation neural network in the USA.

Environmental science and pollution research international
The accurate forecast of carbon dioxide emissions is critical for policy makers to take proper measures to establish a low carbon society. This paper discusses a hybrid of the mixed data sampling (MIDAS) regression model and BP (back propagation) neu...

A fuzzy MICMAC analysis for improving supply chain performance of basic vaccines in developing countries.

Expert review of vaccines
INTRODUCTION: In recent years, demand to improve child immunization coverage globally, and the development of the latest vaccines and technology has made the vaccine market very complex. The rise in such complexities often gives birth to numerous iss...

A Hybrid Semi-Supervised Anomaly Detection Model for High-Dimensional Data.

Computational intelligence and neuroscience
Anomaly detection, which aims to identify observations that deviate from a nominal sample, is a challenging task for high-dimensional data. Traditional distance-based anomaly detection methods compute the neighborhood distance between each observatio...

Using semantics for representing experimental protocols.

Journal of biomedical semantics
BACKGROUND: An experimental protocol is a sequence of tasks and operations executed to perform experimental research in biological and biomedical areas, e.g. biology, genetics, immunology, neurosciences, virology. Protocols often include references t...

Beyond modularity: Fine-scale mechanisms and rules for brain network reconfiguration.

NeuroImage
The human brain is in constant flux, as distinct areas engage in transient communication to support basic behaviors as well as complex cognition. The collection of interactions between cortical and subcortical areas forms a functional brain network w...

Graph-based representation of behavior in detection and prediction of daily living activities.

Computers in biology and medicine
Various surveillance systems capture signs of human activities of daily living (ADLs) and store multimodal information as time line behavioral records. In this paper, we present a novel approach to the analysis of a behavioral record used in a survei...