AIMC Topic: Models, Statistical

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Assessing Dry Weight of Hemodialysis Patients via Sparse Laplacian Regularized RVFL Neural Network with L-Norm.

BioMed research international Feb 4, 2021
Dry weight is the normal weight of hemodialysis patients after hemodialysis. If the amount of water in diabetes is too much (during hemodialysis), the patient will experience hypotension and shock symptoms. Therefore, the correct assessment of the pa...
Humans Blood Pressure Neural Networks, Computer Body Weight Body Weights and Measures Machine Learning Middle Aged Female Aged Adult Male Renal Dialysis Body Mass Index Models, Statistical
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Latent Dirichlet allocation model for world trade analysis.

PloS one Feb 4, 2021
International trade is one of the classic areas of study in economics. Its empirical analysis is a complex problem, given the amount of products, countries and years. Nowadays, given the availability of data, the tools used for the analysis can be co...
Industry Commerce International Cooperation Humans Models, Statistical Databases, Factual Natural Language Processing
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Learning Transferable Driven and Drone Assisted Sustainable and Robust Regional Disease Surveillance for Smart Healthcare.

IEEE/ACM transactions on computational biology and bioinformatics Feb 3, 2021
Smart healthcare has been applied in many fields such as disease surveillance and telemedicine, etc. However, there are some challenges for device deployment, data collection and guarantee of stainability in regional disease surveillance. First, it i...
Humans Machine Learning Algorithms Telemedicine Models, Statistical Unmanned Aerial Devices Public Health Surveillance
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GrantExtractor: Accurate Grant Support Information Extraction from Biomedical Fulltext Based on Bi-LSTM-CRF.

IEEE/ACM transactions on computational biology and bioinformatics Feb 3, 2021
Grant support (GS) in the MEDLINE database refers to funding agencies and contract numbers. It is important for funding organizations to track their funding outcomes from the GS information. As such, how to accurately and automatically extract fundin...
Data Mining MEDLINE National Library of Medicine (U.S.) Financing, Organized Deep Learning United States Models, Statistical
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CrystalM: A Multi-View Fusion Approach for Protein Crystallization Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Feb 3, 2021
Improving the accuracy of predicting protein crystallization is very important for protein crystallization projects, which is a critical step for the determination of protein structure by X-ray crystallography. At present, many machine learning metho...
Proteins Sequence Analysis, Protein Crystallization Computational Biology Position-Specific Scoring Matrices Support Vector Machine Models, Statistical
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Modeling anxiety and fear of COVID-19 using machine learning in a sample of Chinese adults: associations with psychopathology, sociodemographic, and exposure variables.

Anxiety, stress, and coping Jan 26, 2021
OBJECTIVES: Research during prior virus outbreaks has examined vulnerability factors associated with increased anxiety and fear.
COVID-19 Female Humans Machine Learning Socioeconomic Factors Male Models, Statistical Anxiety Disorders Fear SARS-CoV-2 China Mass Media Surveys and Questionnaires Adult Cross-Sectional Studies
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Catch Me if You Can: Acute Events Hidden in Structured Chronic Disease Diagnosis Descriptions Show Detectable Recording Patterns in EHR.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
Our previous research shows that structured cancer DX description data accuracy varied across electronic health record (EHR) segments (e.g. encounter DX, problem list, etc.). We provide initial evidence corroborating these findings in EHRs from patie...
Glycated Hemoglobin Datasets as Topic Diabetes Mellitus Odds Ratio Medical Informatics Humans Models, Statistical Chronic Disease Machine Learning Electronic Health Records
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DeepCompete : A deep learning approach to competing risks in continuous time domain.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
An increasing number of people survive longer ages leading to a growing population of people 65 years of age or older. A large percentage of this population is afflicted with multiple acute diseases (multi-morbidity). Clinicians need new tools to qua...
Models, Statistical Survival Analysis Risk Aged Deep Learning Humans
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Quantification of Key Retinal Features in Early and Late Age-Related Macular Degeneration Using Deep Learning.

American journal of ophthalmology Jan 8, 2021
PURPOSE: We sought to develop and validate a deep learning model for segmentation of 13 features associated with neovascular and atrophic age-related macular degeneration (AMD).
Receptors, Vascular Endothelial Growth Factor Retinal Drusen Choroidal Neovascularization Geographic Atrophy Recombinant Fusion Proteins Ranibizumab Wet Macular Degeneration ROC Curve Angiogenesis Inhibitors Models, Statistical Vascular Endothelial Growth Factor A Intravitreal Injections Visual Acuity Tomography, Optical Coherence Male Middle Aged Deep Learning Aged Aged, 80 and over Sensitivity and Specificity Neural Networks, Computer Female Humans
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Prediction of Clinical Outcome in Patients with Large-Vessel Acute Ischemic Stroke: Performance of Machine Learning versus SPAN-100.

AJNR. American journal of neuroradiology Jan 7, 2021
BACKGROUND AND PURPOSE: Traditional statistical models and pretreatment scoring systems have been used to predict the outcome for acute ischemic stroke patients (AIS). Our aim was to select the most relevant features in terms of outcome prediction on...
Retrospective Studies Female Aged Male Humans Machine Learning Prognosis Models, Statistical Ischemic Stroke Thrombolytic Therapy Endovascular Procedures Middle Aged Cohort Studies Treatment Outcome
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