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ROC Curve

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CRNNTL: Convolutional Recurrent Neural Network and Transfer Learning for QSAR Modeling in Organic Drug and Material Discovery.

Molecules (Basel, Switzerland) Nov 30, 2021
Molecular latent representations, derived from autoencoders (AEs), have been widely used for drug or material discovery over the past couple of years. In particular, a variety of machine learning methods based on latent representations have shown exc...
Models, Theoretical Databases as Topic Neural Networks, Computer Regression Analysis Quantitative Structure-Activity Relationship Drug Discovery Area Under Curve Binding Sites ROC Curve Isomerism Organic Chemicals
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Using k-mer embeddings learned from a Skip-gram based neural network for building a cross-species DNA N6-methyladenine site prediction model.

Plant molecular biology Nov 29, 2021
This study used k-mer embeddings as effective feature to identify DNA N6-Methyladenine sites in plant genomes and obtained improved performance without substantial effort in feature extraction, combination and selection. Identification of DNA N6-meth...
Nucleotides Neural Networks, Computer Base Sequence ROC Curve Algorithms Adenine Databases, Genetic Surveys and Questionnaires DNA, Plant Models, Biological Plants
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Mental Stress Classification Based on a Support Vector Machine and Naive Bayes Using Electrocardiogram Signals.

Sensors (Basel, Switzerland) Nov 27, 2021
Examining mental health is crucial for preventing mental illnesses such as depression. This study presents a method for classifying electrocardiogram (ECG) data into four emotional states according to the stress levels using one-against-all and naive...
Humans Bayes Theorem Algorithms ROC Curve Electrocardiography Support Vector Machine
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Artificial intelligence modelling in differentiating core biopsies of fibroadenoma from phyllodes tumor.

Laboratory investigation; a journal of technical methods and pathology Nov 24, 2021
Breast fibroepithelial lesions (FEL) are biphasic tumors which consist of benign fibroadenomas (FAs) and the rarer phyllodes tumors (PTs). FAs and PTs have overlapping features, but have different clinical management, which makes correct core biopsy ...
ROC Curve Diagnosis, Differential Breast Biopsy, Large-Core Needle Fibroadenoma Phyllodes Tumor Neural Networks, Computer Artificial Intelligence Female Breast Neoplasms Humans
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Machine learning-based Radiomics analysis for differentiation degree and lymphatic node metastasis of extrahepatic cholangiocarcinoma.

BMC cancer Nov 24, 2021
BACKGROUND: Radiomics may provide more objective and accurate predictions for extrahepatic cholangiocarcinoma (ECC). In this study, we developed radiomics models based on magnetic resonance imaging (MRI) and machine learning to preoperatively predict...
Bile Duct Neoplasms Cholangiocarcinoma Humans Machine Learning Middle Aged ROC Curve Adenocarcinoma Lymphatic Metastasis Magnetic Resonance Imaging Predictive Value of Tests Algorithms Aged, 80 and over Area Under Curve Retrospective Studies Neoplasm Grading Adult Sensitivity and Specificity Female Male Aged
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A Comparison of Models Predicting One-Year Mortality at Time of Admission.

Journal of pain and symptom management Nov 23, 2021
CONTEXT: Hospitalization provides an opportunity to address end-of-life care (EoLC) preferences if patients at risk of death can be accurately identified while in the hospital. The modified Hospital One-Year Mortality Risk (mHOMR) uses demographic an...
Hospital Mortality ROC Curve Logistic Models Humans Machine Learning Retrospective Studies Hospitalization
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The new SUMPOT to predict postoperative complications using an Artificial Neural Network.

Scientific reports Nov 22, 2021
An accurate assessment of preoperative risk may improve use of hospital resources and reduce morbidity and mortality in high-risk surgical patients. This study aims at implementing an automated surgical risk calculator based on Artificial Neural Netw...
Emergency Treatment ROC Curve Predictive Value of Tests Area Under Curve Elective Surgical Procedures Female Risk Factors Hospitalization Male Middle Aged Risk Assessment Postoperative Complications Cohort Studies Machine Learning Prognosis Retrospective Studies Intensive Care Units Humans Neural Networks, Computer
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Machine learning approach for the prediction of postpartum hemorrhage in vaginal birth.

Scientific reports Nov 19, 2021
Postpartum hemorrhage is the leading cause of maternal morbidity. Clinical prediction of postpartum hemorrhage remains challenging, particularly in the case of a vaginal birth. We studied machine learning models to predict postpartum hemorrhage. Wome...
ROC Curve Humans Logistic Models Neural Networks, Computer Models, Theoretical Postpartum Hemorrhage Support Vector Machine Adult Machine Learning Delivery, Obstetric Models, Statistical Pregnancy Female Middle Aged Labor, Obstetric Area Under Curve Infant, Newborn Tokyo Deep Learning False Positive Reactions Reproducibility of Results Adolescent Risk Young Adult
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The prediction of surgical complications using artificial intelligence in patients undergoing major abdominal surgery: A systematic review.

Surgery Nov 18, 2021
BACKGROUND: Conventional statistics are based on a simple cause-and-effect principle. Postoperative complications, however, have a multifactorial and interrelated etiology. The application of artificial intelligence might be more accurate to predict ...
Humans Artificial Intelligence Algorithms Postoperative Complications ROC Curve
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Can we predict anti-seizure medication response in focal epilepsy using machine learning?

Clinical neurology and neurosurgery Nov 16, 2021
OBJECTIVE: The aim of this study was to evaluate the feasibility of machine learning approach based on clinical factors and diffusion tensor imaging (DTI) to predict anti-seizure medication (ASM) response in focal epilepsy. We hypothesized that ASM r...
Retrospective Studies Female Young Adult Adult Humans Machine Learning Male Predictive Value of Tests Middle Aged Anticonvulsants ROC Curve Diffusion Tensor Imaging Treatment Outcome Epilepsies, Partial
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