Models, Statistical

HetEnc: a deep learning predictive model for multi-type biological dataset.

BMC genomics Aug 8, 2019

BACKGROUND: Researchers today are generating unprecedented amounts of biological data. One trend in current biological research is integrated analysis with multi-platform data. Effective integration of multi-platform data into the solution of a singl...

Humans Databases, Factual Transcriptome Deep Learning Computational Biology Models, Statistical Unsupervised Machine Learning Neuroblastoma

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Machine learning with the hierarchy-of-hypotheses (HoH) approach discovers novel pattern in studies on biological invasions.

Research synthesis methods Aug 5, 2019

Research synthesis on simple yet general hypotheses and ideas is challenging in scientific disciplines studying highly context-dependent systems such as medical, social, and biological sciences. This study shows that machine learning, equation-free s...

Reproducibility of Results Animals Ecology Ecosystem Asia Models, Statistical Geography Decision Trees Introduced Species Data Interpretation, Statistical Artificial Intelligence Review Literature as Topic Biology Machine Learning Algorithms Research Design

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Comparison of machine learning algorithms for clinical event prediction (risk of coronary heart disease).

Journal of biomedical informatics Jul 30, 2019

AIM: The aim of this study is to compare the utility of several supervised machine learning (ML) algorithms for predicting clinical events in terms of their internal validity and accuracy. The results, which were obtained using two statistical softwa...

Prospective Studies Area Under Curve Support Vector Machine Risk Factors Humans Supervised Machine Learning Computational Biology Longitudinal Studies Neural Networks, Computer Coronary Disease Logistic Models Models, Statistical Algorithms Decision Trees Databases, Factual

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Accurate and interpretable evaluation of surgical skills from kinematic data using fully convolutional neural networks.

International journal of computer assisted radiology and surgery Jul 30, 2019

PURPOSE: Manual feedback from senior surgeons observing less experienced trainees is a laborious task that is very expensive, time-consuming and prone to subjectivity. With the number of surgical procedures increasing annually, there is an unpreceden...

Surgeons General Surgery Humans Regression Analysis Neural Networks, Computer Clinical Competence Robotic Surgical Procedures Machine Learning Cluster Analysis Motion Feedback Models, Statistical Markov Chains Biomechanical Phenomena

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G-DipC: An Improved Feature Representation Method for Short Sequences to Predict the Type of Cargo in Cell-Penetrating Peptides.

IEEE/ACM transactions on computational biology and bioinformatics Jul 25, 2019

Cell-penetrating peptides (CPPs) are functional short peptides with high carrying capacity. CPP sequences with targeting functions for the highly efficient delivery of drugs to target cells. In this paper, which is focused on the prediction of the ca...

Support Vector Machine Models, Statistical Machine Learning Discriminant Analysis Algorithms Cell-Penetrating Peptides Computational Biology

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Region-of-interest undersampled MRI reconstruction: A deep convolutional neural network approach.

Magnetic resonance imaging Jul 25, 2019

Compressive sensing enables fast magnetic resonance imaging (MRI) reconstruction with undersampled k-space data. However, in most existing MRI reconstruction models, the whole MR image is targeted and reconstructed without taking specific tissue regi...

Image Processing, Computer-Assisted Magnetic Resonance Imaging Models, Statistical Brain Mapping Data Compression Humans Neural Networks, Computer Computers Brain

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Machine learning and statistical models for predicting indoor air quality.

Indoor air Jul 25, 2019

Indoor air quality (IAQ), as determined by the concentrations of indoor air pollutants, can be predicted using either physically based mechanistic models or statistical models that are driven by measured data. In comparison with mechanistic models mo...

Humans Regression Analysis Decision Trees Air Pollutants Neural Networks, Computer Air Pollution, Indoor Machine Learning Environmental Monitoring Models, Statistical

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Readmission prediction using deep learning on electronic health records.

Journal of biomedical informatics Jul 24, 2019

Unscheduled 30-day readmissions are a hallmark of Congestive Heart Failure (CHF) patients that pose significant health risks and escalate care cost. In order to reduce readmissions and curb the cost of care, it is important to initiate targeted inter...

Computational Biology Models, Statistical Humans Patient Discharge Neural Networks, Computer Heart Failure Electronic Health Records Patient Readmission Aged, 80 and over Female Expert Systems Male Sweden Cost Savings Deep Learning Risk Factors Time Factors Aged

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Machine Learning-Based Predictive Modeling of Surgical Intervention in Glaucoma Using Systemic Data From Electronic Health Records.

American journal of ophthalmology Jul 16, 2019

PURPOSE: To predict the need for surgical intervention in patients with primary open-angle glaucoma (POAG) using systemic data in electronic health records (EHRs).

Filtering Surgery Intraocular Pressure Male Middle Aged Disease Progression ROC Curve Models, Statistical Odds Ratio Glaucoma, Open-Angle Reproducibility of Results Aged Aged, 80 and over Sensitivity and Specificity Machine Learning Retrospective Studies Electronic Health Records Female Humans

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Development and validation of 15-month mortality prediction models: a retrospective observational comparison of machine-learning techniques in a national sample of Medicare recipients.

BMJ open Jul 16, 2019

OBJECTIVE: The objective is to develop and validate a predictive model for 15-month mortality using a random sample of community-dwelling Medicare beneficiaries.

Female Aged Aged, 80 and over Male Humans Neural Networks, Computer Machine Learning Bayes Theorem Medicare Mortality Logistic Models United States Models, Statistical Decision Trees

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AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

HetEnc: a deep learning predictive model for multi-type biological dataset.

Machine learning with the hierarchy-of-hypotheses (HoH) approach discovers novel pattern in studies on biological invasions.

Comparison of machine learning algorithms for clinical event prediction (risk of coronary heart disease).

Accurate and interpretable evaluation of surgical skills from kinematic data using fully convolutional neural networks.

G-DipC: An Improved Feature Representation Method for Short Sequences to Predict the Type of Cargo in Cell-Penetrating Peptides.

Region-of-interest undersampled MRI reconstruction: A deep convolutional neural network approach.

Machine learning and statistical models for predicting indoor air quality.

Readmission prediction using deep learning on electronic health records.

Machine Learning-Based Predictive Modeling of Surgical Intervention in Glaucoma Using Systemic Data From Electronic Health Records.

Development and validation of 15-month mortality prediction models: a retrospective observational comparison of machine-learning techniques in a national sample of Medicare recipients.

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