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Predicting essential genes of 41 prokaryotes by a semi-supervised method.

Analytical biochemistry Aug 19, 2020
Essential genes are vitally important to the survival and reproduction of organisms. Many machine learning methods have been widely employed to predict essential genes and have obtained satisfactory results. However, most of these methods are supervi...
ROC Curve Genes, Essential Databases, Genetic Area Under Curve Supervised Machine Learning Prokaryotic Cells
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Using Machine Learning to Make Predictions in Patients Who Fall.

The Journal of surgical research Aug 18, 2020
BACKGROUND: As the population ages, the incidence of traumatic falls has been increasing. We hypothesize that a machine learning algorithm can more accurately predict mortality after a fall compared with a standard logistic regression (LR) model base...
Male Middle Aged Length of Stay Accidental Falls ROC Curve Decision Trees Patient Discharge Injury Severity Score Female Aged Aged, 80 and over Adult Humans Machine Learning Algorithms Retrospective Studies Trauma Centers Intensive Care Units Glasgow Coma Scale
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Utilization of machine-learning models to accurately predict the risk for critical COVID-19.

Internal and emergency medicine Aug 18, 2020
Among patients with Coronavirus disease (COVID-19), the ability to identify patients at risk for deterioration during their hospital stay is essential for effective patient allocation and management. To predict patient risk for critical COVID-19 base...
Coronavirus Infections APACHE Pneumonia, Viral Female Pandemics Middle Aged Hospitalization COVID-19 Risk Assessment Aged Retrospective Studies ROC Curve Aged, 80 and over Critical Illness Adult Male Humans Machine Learning
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m7GPredictor: An improved machine learning-based model for predicting internal m7G modifications using sequence properties.

Analytical biochemistry Aug 14, 2020
As one of the most important post-transcriptional modifications, the N7-methylguanosine (m7G) plays a key role in many RNA processing events. The accurate identification of m7G is crucial for elucidating its biological significance and future applica...
ROC Curve Models, Theoretical Support Vector Machine Databases, Genetic Machine Learning User-Computer Interface Area Under Curve Guanosine
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Deep Learning Modeling of Androgen Receptor Responses to Prostate Cancer Therapies.

International journal of molecular sciences Aug 14, 2020
Gain-of-function mutations in human androgen receptor (AR) are among the major causes of drug resistance in prostate cancer (PCa). Identifying mutations that cause resistant phenotype is of critical importance for guiding treatment protocols, as well...
Humans Neural Networks, Computer Male Deep Learning Receptors, Androgen Transcription, Genetic Androgen Receptor Antagonists Cell Line, Tumor ROC Curve Prostatic Neoplasms Mutation
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Time-series cardiovascular risk factors and receipt of screening for breast, cervical, and colon cancer: The Guideline Advantage.

PloS one Aug 13, 2020
BACKGROUND: Cancer is the second leading cause of death in the United States. Cancer screenings can detect precancerous cells and allow for earlier diagnosis and treatment. Our purpose was to better understand risk factors for cancer screenings and a...
Deep Learning Breast Neoplasms Colonic Neoplasms Humans ROC Curve Guidelines as Topic Uterine Cervical Neoplasms Female Early Detection of Cancer Cardiovascular Diseases Risk Factors Area Under Curve Middle Aged Adult
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Machine Learning Prediction of Stroke Mechanism in Embolic Strokes of Undetermined Source.

Stroke Aug 12, 2020
BACKGROUND AND PURPOSE: One-fifth of ischemic strokes are embolic strokes of undetermined source (ESUS). Their theoretical causes can be classified as cardioembolic versus noncardioembolic. This distinction has important implications, but the categor...
Decision Trees Predictive Value of Tests Registries Stroke Middle Aged ROC Curve Image Processing, Computer-Assisted Electrocardiography Atrial Fibrillation Intracranial Embolism Humans Reproducibility of Results Machine Learning Aged Algorithms Aged, 80 and over Female Male
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A Linear Regression and Deep Learning Approach for Detecting Reliable Genetic Alterations in Cancer Using DNA Methylation and Gene Expression Data.

Genes Aug 12, 2020
DNA methylation change has been useful for cancer biomarker discovery, classification, and potential treatment development. So far, existing methods use either differentially methylated CpG sites or combined CpG sites, namely differentially methylate...
Linear Models Gene Ontology Deep Learning ROC Curve Computational Biology Epigenesis, Genetic Algorithms Gene Expression Regulation, Neoplastic Biomarkers, Tumor Databases, Genetic Neoplasms DNA Methylation Gene Expression Profiling Genetic Variation Humans
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Comparing different deep learning architectures for classification of chest radiographs.

Scientific reports Aug 12, 2020
Chest radiographs are among the most frequently acquired images in radiology and are often the subject of computer vision research. However, most of the models used to classify chest radiographs are derived from openly available deep neural networks,...
Pandemics COVID-19 SARS-CoV-2 Sensitivity and Specificity Humans Neural Networks, Computer Radiography, Thoracic Thorax Betacoronavirus Pneumonia, Viral Diagnosis, Computer-Assisted Deep Learning ROC Curve Coronavirus Infections
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Development of a Deep Learning-Based Model for Diagnosing Breast Nodules With Ultrasound.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine Aug 8, 2020
OBJECTIVES: Artificial intelligence (AI) has been an important addition to medicine. We aimed to explore the use of deep learning (DL) to distinguish benign from malignant lesions with breast ultrasound (BUS).
Female Sensitivity and Specificity Deep Learning Ultrasonography ROC Curve Humans Artificial Intelligence
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