AI Medical Compendium Topic:
Models, Theoretical

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Precursor-induced conditional random fields: connecting separate entities by induction for improved clinical named entity recognition.

BMC medical informatics and decision making
BACKGROUND: This paper presents a conditional random fields (CRF) method that enables the capture of specific high-order label transition factors to improve clinical named entity recognition performance. Consecutive clinical entities in a sentence ar...

Employing a Fuzzy-Based Grey Modeling Procedure to Forecast China's Sulfur Dioxide Emissions.

International journal of environmental research and public health
Effective determination of trends in sulfur dioxide emissions facilitates national efforts to draft an appropriate policy that aims to lower sulfur dioxide emissions, which is essential for reducing atmospheric pollution. However, to reflect the curr...

AI- modelling of molecular identification and feminization of wolbachia infected Aedes aegypti.

Progress in biophysics and molecular biology
BACKGROUND: The genetic control strategies of vector borne diseases includes the replacement of a vector population by "disease-refractory" mosquitoes and the release of mosquitoes with a gene to control the vector's reproduction rates. Wolbachia are...

Classification of alkaloids according to the starting substances of their biosynthetic pathways using graph convolutional neural networks.

BMC bioinformatics
BACKGROUND: Alkaloids, a class of organic compounds that contain nitrogen bases, are mainly synthesized as secondary metabolites in plants and fungi, and they have a wide range of bioactivities. Although there are thousands of compounds in this class...

Deep Reinforcement Learning for Multiparameter Optimization in Drug Design.

Journal of chemical information and modeling
In medicinal chemistry programs it is key to design and make compounds that are efficacious and safe. This is a long, complex, and difficult multiparameter optimization process, often including several properties with orthogonal trends. New methods f...

BioGD: Bio-inspired robust gradient descent.

PloS one
Recent research in machine learning pointed to the core problem of state-of-the-art models which impedes their widespread adoption in different domains. The models' inability to differentiate between noise and subtle, yet significant variation in dat...

Learning-based classification of valence emotion from electroencephalography.

The International journal of neuroscience
The neuroimaging research field has been revolutionized with the development of human cognitive functions without the use of brain pathways. To assist such systems, electroencephalography (EEG) based measures play an important role. In this study, th...

Adaptive fractional fuzzy sliding mode control of microgyroscope based on backstepping design.

PloS one
In this paper, a robust sliding mode control (SMC) based on backstepping technique is studied for a microgyroscope in the presence of unknown model uncertainties and external disturbances using adaptive fuzzy compensator and fractional calculus. At f...

Machine learning techniques for personalized breast cancer risk prediction: comparison with the BCRAT and BOADICEA models.

Breast cancer research : BCR
BACKGROUND: Comprehensive breast cancer risk prediction models enable identifying and targeting women at high-risk, while reducing interventions in those at low-risk. Breast cancer risk prediction models used in clinical practice have low discriminat...

MetaNN: accurate classification of host phenotypes from metagenomic data using neural networks.

BMC bioinformatics
BACKGROUND: Microbiome profiles in the human body and environment niches have become publicly available due to recent advances in high-throughput sequencing technologies. Indeed, recent studies have already identified different microbiome profiles in...