AIMC Topic:
Models, Theoretical

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Big Data Analytics + Virtual Clinical Semantic Network (vCSN): An Approach to Addressing the Increasing Clinical Nuances and Organ Involvement of COVID-19.

ASAIO journal (American Society for Artificial Internal Organs : 1992) Jan 1, 2021
The coronavirus disease 2019 (COVID-19) pandemic has revealed deep gaps in our understanding of the clinical nuances of this extremely infectious viral pathogen. In order for public health, care delivery systems, clinicians, and other stakeholders to...
COVID-19 Reproducibility of Results Big Data Humans Artificial Intelligence Machine Learning Semantics Symptom Assessment Semantic Web Data Science Models, Theoretical Medical Informatics
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The emergence of new trends in clinical laboratory diagnosis.

Saudi medical journal Nov 1, 2020
Diagnostic processes typically rely on traditional and laborious methods, that are prone to human error, resulting in frequent misdiagnosis of diseases. Computational approaches are being increasingly used for more precise diagnosis of the clinical p...
Clinical Laboratory Techniques Confidentiality Databases as Topic Chemistry, Clinical Humans Artificial Intelligence Reproducibility of Results Diagnostic Errors Models, Theoretical
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Routine Laboratory Blood Tests Predict SARS-CoV-2 Infection Using Machine Learning.

Clinical chemistry Nov 1, 2020
BACKGROUND: Accurate diagnostic strategies to identify SARS-CoV-2 positive individuals rapidly for management of patient care and protection of health care personnel are urgently needed. The predominant diagnostic test is viral RNA detection by RT-PC...
Humans Machine Learning Female Aged Young Adult Pandemics COVID-19 Retrospective Studies Coronavirus Infections COVID-19 Testing Laboratories Reverse Transcriptase Polymerase Chain Reaction Hematologic Tests ROC Curve Clinical Laboratory Techniques Models, Theoretical Adult Male Middle Aged Pneumonia, Viral
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Modern deep learning in bioinformatics.

Journal of molecular cell biology Oct 30, 2020
Publications Deep Learning Computational Biology Models, Theoretical
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TMLRpred: A machine learning classification model to distinguish reversible EGFR double mutant inhibitors.

Chemical biology & drug design Sep 1, 2020
The EGFR is a clinically important therapeutic drug target in lung cancer. The first-generation tyrosine kinase inhibitors used in clinics are effective against L858R-mutated EGFR. However, relapse of the disease due to the presence of resistant muta...
Mutation Datasets as Topic ErbB Receptors Humans Machine Learning Models, Theoretical
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AI on a chip.

Lab on a chip Aug 26, 2020
Artificial intelligence (AI) has dramatically changed the landscape of science, industry, defence, and medicine in the last several years. Supported by considerably enhanced computational power and cloud storage, the field of AI has shifted from most...
Algorithms Models, Theoretical Lab-On-A-Chip Devices Humans Artificial Intelligence Machine Learning
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Risk prediction of delirium in hospitalized patients using machine learning: An implementation and prospective evaluation study.

Journal of the American Medical Informatics Association : JAMIA Jul 1, 2020
OBJECTIVE: Machine learning models trained on electronic health records have achieved high prognostic accuracy in test datasets, but little is known about their embedding into clinical workflows. We implemented a random forest-based algorithm to iden...
Aged Aged, 80 and over Male Middle Aged Risk Assessment ROC Curve Electronic Health Records Female Humans Hospitalization Machine Learning Algorithms Prospective Studies Models, Theoretical Workflow Delirium
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Categorization of digitized artworks by media with brain programming.

Applied optics May 10, 2020
This work describes the use of brain programming applied to the categorization problem of art media. The art categorization problem-from the standpoint of materials and techniques used by artists-presents a challenging task and is considered an open ...
Cognition Databases, Factual Choice Behavior Humans Models, Theoretical Brain Machine Learning Paintings Computer Simulation
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Parsimonious Minimal Learning Machine via Multiresponse Sparse Regression.

International journal of neural systems May 1, 2020
The training procedure of the minimal learning machine (MLM) requires the selection of two sets of patterns from the training dataset. These sets are called input reference points (IRP) and output reference points (ORP), which are used to build a map...
Models, Theoretical Regression Analysis Pattern Recognition, Automated Humans Machine Learning
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Multi-dimensional machine learning approaches for fruit shape phenotyping in strawberry.

GigaScience May 1, 2020
BACKGROUND: Shape is a critical element of the visual appeal of strawberry fruit and is influenced by both genetic and non-genetic determinants. Current fruit phenotyping approaches for external characteristics in strawberry often rely on the human e...
Machine Learning Genetic Association Studies Fragaria Algorithms Models, Theoretical Inheritance Patterns Phenotype Fruit
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