AIMC Topic: Markov Chains

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Multi-feature data repository development and analytics for image cosegmentation in high-throughput plant phenotyping.

PloS one Sep 2, 2021
Cosegmentation is a newly emerging computer vision technique used to segment an object from the background by processing multiple images at the same time. Traditional plant phenotyping analysis uses thresholding segmentation methods which result in h...
Benchmarking Crop Production Deep Learning Humans Helianthus Image Processing, Computer-Assisted Phenotype Markov Chains Cluster Analysis Fagopyrum Crops, Agricultural
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Accurate Identification of Antioxidant Proteins Based on a Combination of Machine Learning Techniques and Hidden Markov Model Profiles.

Computational and mathematical methods in medicine Aug 7, 2021
Antioxidant proteins (AOPs) play important roles in the management and prevention of several human diseases due to their ability to neutralize excess free radicals. However, the identification of AOPs by using wet-lab experimental techniques is often...
Computational Biology Antioxidants Evolution, Molecular Humans Markov Chains Proteins Machine Learning Peroxiredoxins Databases, Protein Algorithms Amino Acids
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ASNet: Auto-Augmented Siamese Neural Network for Action Recognition.

Sensors (Basel, Switzerland) Jul 10, 2021
Human action recognition methods in videos based on deep convolutional neural networks usually use random cropping or its variants for data augmentation. However, this traditional data augmentation approach may generate many non-informative samples (...
Markov Chains Human Activities Recognition, Psychology Humans Neural Networks, Computer Learning
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Physics-based protein structure refinement in the era of artificial intelligence.

Proteins Jun 29, 2021
Protein structure refinement is the last step in protein structure prediction pipelines. Physics-based refinement via molecular dynamics (MD) simulations has made significant progress during recent years. During CASP14, we tested a new refinement pro...
Markov Chains Protein Conformation Physical Phenomena Computational Biology Proteins Molecular Dynamics Simulation Artificial Intelligence Software
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A machine learning approach to predict healthcare cost of breast cancer patients.

Scientific reports Jun 14, 2021
This paper presents a novel machine learning approach to perform an early prediction of the healthcare cost of breast cancer patients. The learning phase of our prediction method considers the following two steps: (1) in the first step, the patients ...
Female Breast Neoplasms Cluster Analysis Humans Machine Learning Electronic Health Records Markov Chains Models, Economic Health Care Costs
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Cost Effectiveness of an Electrocardiographic Deep Learning Algorithm to Detect Asymptomatic Left Ventricular Dysfunction.

Mayo Clinic proceedings Jun 9, 2021
OBJECTIVE: To evaluate the cost-effectiveness of an artificial intelligence electrocardiogram (AI-ECG) algorithm under various clinical and cost scenarios when used for universal screening at age 65.
Quality-Adjusted Life Years Ventricular Dysfunction, Left Asymptomatic Diseases Mass Screening Cost-Benefit Analysis Markov Chains Female Aged Male Middle Aged Deep Learning Electrocardiography Humans Artificial Intelligence Algorithms
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Emotions of COVID-19: Content Analysis of Self-Reported Information Using Artificial Intelligence.

Journal of medical Internet research Apr 30, 2021
BACKGROUND: The COVID-19 pandemic has disrupted human societies around the world. This public health emergency was followed by a significant loss of human life; the ensuing social restrictions led to loss of employment, lack of interactions, and burg...
Self Report Markov Chains Psychological Distress Sadness Emotions Social Media Natural Language Processing Mental Health Communication Humans Pandemics COVID-19
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Computational medication regimen for Parkinson's disease using reinforcement learning.

Scientific reports Apr 29, 2021
Our objective is to derive a sequential decision-making rule on the combination of medications to minimize motor symptoms using reinforcement learning (RL). Using an observational longitudinal cohort of Parkinson's disease patients, the Parkinson's P...
Female Aged Male Middle Aged Cohort Studies Parkinson Disease Humans Machine Learning Markov Chains Drug Therapy, Combination
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Clone-structured graph representations enable flexible learning and vicarious evaluation of cognitive maps.

Nature communications Apr 22, 2021
Cognitive maps are mental representations of spatial and conceptual relationships in an environment, and are critical for flexible behavior. To form these abstract maps, the hippocampus has to learn to separate or merge aliased observations appropria...
Models, Neurological Neural Networks, Computer Markov Chains Learning Hippocampus Cognition Humans
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H estimation for stochastic semi-Markovian switching CVNNs with missing measurements and mode-dependent delays.

Neural networks : the official journal of the International Neural Network Society Apr 21, 2021
This article is devoted to the H estimation problem for stochastic semi-Markovian switching complex-valued neural networks subject to incomplete measurement outputs, where the time-varying delay also depends on another semi-Markov process. A sequence...
Neural Networks, Computer Markov Chains Algorithms Computer Simulation
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