AIMC Topic:
Models, Theoretical

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Venn diagrams in bioinformatics.

Briefings in bioinformatics Sep 2, 2021
Venn diagrams are widely used tools for graphical depiction of the unions, intersections and distinctions among multiple datasets, and a large number of programs have been developed to generate Venn diagrams for applications in various research areas...
Computer Graphics Gene Expression Profiling Gene Regulatory Networks Computational Biology Models, Theoretical Databases, Genetic Gene Ontology Humans Software Animals
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Feature extraction approaches for biological sequences: a comparative study of mathematical features.

Briefings in bioinformatics Sep 2, 2021
As consequence of the various genomic sequencing projects, an increasing volume of biological sequence data is being produced. Although machine learning algorithms have been successfully applied to a large number of genomic sequence-related problems,...
Computational Biology RNA, Messenger Models, Theoretical Fourier Analysis Humans RNA, Long Noncoding Open Reading Frames Deep Learning Base Sequence RNA, Circular Entropy
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Hysteresis modeling and compensation of a rotary series elastic actuator with nonlinear stiffness.

The Review of scientific instruments Sep 1, 2021
Series elastic actuators (SEAs) have widely been adapted in robots where safe human-robot interaction is required for accurate and robust force control. Recent research on the SEAs has shown that the SEA with a user-defined variable stiffness possess...
Robotics Equipment Design Torque Humans Models, Theoretical Nonlinear Dynamics
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Evaluation of the prediction of CoVID-19 recovered and unrecovered cases using symptoms and patient's meta data based on support vector machine, neural network, CHAID and QUEST Models.

European review for medical and pharmacological sciences Sep 1, 2021
OBJECTIVE: This paper aims to develop four prediction models for recovered and unrecovered cases using descriptive data of patients and symptoms of CoVID-19 patients. The developed prediction models aim to extract the important variables in predictin...
COVID-19 SARS-CoV-2 Models, Theoretical Humans Neural Networks, Computer Support Vector Machine Metadata Symptom Assessment
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Auto informing COVID-19 detection result from x-ray/CT images based on deep learning.

The Review of scientific instruments Aug 1, 2021
It is no secret to all that the corona pandemic has caused a decline in all aspects of the world. Therefore, offering an accurate automatic diagnostic system is very important. This paper proposed an accurate COVID-19 system by testing various deep l...
Models, Theoretical Humans COVID-19 Tomography, X-Ray Computed SARS-CoV-2 Lung Deep Learning
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Unsupervised flow cytometry analysis in hematological malignancies: A new paradigm.

International journal of laboratory hematology Jul 1, 2021
Ever since hematopoietic cells became "events" enumerated and characterized in suspension by cell counters or flow cytometers, researchers and engineers have strived to refine the acquisition and display of the electronic signals generated. A large a...
Software Algorithms Hematologic Neoplasms Disease Progression Computational Biology Bone Marrow Models, Theoretical Cluster Analysis Humans Unsupervised Machine Learning Flow Cytometry
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Predicting the Need For Vasopressors in the Intensive Care Unit Using an Attention Based Deep Learning Model.

Shock (Augusta, Ga.) Jul 1, 2021
BACKGROUND: Previous models on prediction of shock mostly focused on septic shock and often required laboratory results in their models. The purpose of this study was to use deep learning approaches to predict vasopressor requirement for critically i...
Vasoconstrictor Agents Vital Signs Needs Assessment Deep Learning Cohort Studies Models, Theoretical Critical Illness Intensive Care Units Female Aged Male Middle Aged Humans Retrospective Studies
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From COVID-19 to future electrification: Assessing traffic impacts on air quality by a machine-learning model.

Proceedings of the National Academy of Sciences of the United States of America Jun 29, 2021
The large fluctuations in traffic during the COVID-19 pandemic provide an unparalleled opportunity to assess vehicle emission control efficacy. Here we develop a random-forest regression model, based on the large volume of real-time observational dat...
Particulate Matter Humans Vehicle Emissions Electricity Machine Learning Models, Theoretical Transportation COVID-19 Air Pollutants Algorithms Air Pollution
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Pretraining model for biological sequence data.

Briefings in functional genomics Jun 9, 2021
With the development of high-throughput sequencing technology, biological sequence data reflecting life information becomes increasingly accessible. Particularly on the background of the COVID-19 pandemic, biological sequence data play an important r...
High-Throughput Nucleotide Sequencing Datasets as Topic Models, Theoretical Natural Language Processing Data Mining Algorithms Humans Deep Learning Software Computational Biology
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Artificial Intelligence-related Literature in Transplantation: A Practical Guide.

Transplantation Apr 1, 2021
Data Mining Biomedical Research Humans Transplantation Big Data Artificial Intelligence Models, Theoretical Databases, Factual
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