AIMC Topic: ROC Curve

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A practical model for the identification of congenital cataracts using machine learning.

EBioMedicine Jan 3, 2020
BACKGROUND: Approximately 1 in 33 newborns is affected by congenital anomalies worldwide. We aimed to develop a practical model for identifying infants with a high risk of congenital cataracts (CCs), which is the leading cause of avoidable childhood ...
Female Reproducibility of Results Risk Factors Male Humans Machine Learning Algorithms Case-Control Studies Child, Preschool ROC Curve Models, Biological Inheritance Patterns Area Under Curve Cataract
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Using transfer learning from prior reference knowledge to improve the clustering of single-cell RNA-Seq data.

Scientific reports Dec 30, 2019
In many research areas scientists are interested in clustering objects within small datasets while making use of prior knowledge from large reference datasets. We propose a method to apply the machine learning concept of transfer learning to unsuperv...
Machine Learning Algorithms Reproducibility of Results ROC Curve Single-Cell Analysis Gene Expression Profiling Transcriptome Humans High-Throughput Nucleotide Sequencing Computational Biology Sequence Analysis, RNA Cluster Analysis
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Automatic detection of blood content in capsule endoscopy images based on a deep convolutional neural network.

Journal of gastroenterology and hepatology Dec 27, 2019
BACKGROUND AND AIM: Detecting blood content in the gastrointestinal tract is one of the crucial applications of capsule endoscopy (CE). The suspected blood indicator (SBI) is a conventional tool used to automatically tag images depicting possible ble...
Sensitivity and Specificity Deep Learning ROC Curve Intestine, Small Blood Area Under Curve Capsule Endoscopy Humans Neural Networks, Computer Retrospective Studies
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Comparison of the predictive outcomes for anti-tuberculosis drug-induced hepatotoxicity by different machine learning techniques.

Computer methods and programs in biomedicine Dec 27, 2019
BACKGROUND: The study compared the predictive outcomes of artificial neural network, support vector machine and random forest on the occurrence of anti-tuberculosis drug-induced hepatotoxicity.
Gene Frequency Polymorphism, Genetic Chemical and Drug Induced Liver Injury Taiwan Antitubercular Agents Tuberculosis Machine Learning Female Humans Neural Networks, Computer Aged, 80 and over Adult Sensitivity and Specificity Male Reproducibility of Results Risk Factors Aged Genomics Genotype Support Vector Machine Liver Middle Aged Drug Discovery ROC Curve
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Identification of self-interacting proteins by integrating random projection classifier and finite impulse response filter.

BMC genomics Dec 27, 2019
BACKGROUND: Identification of protein-protein interactions (PPIs) is crucial for understanding biological processes and investigating the cellular functions of genes. Self-interacting proteins (SIPs) are those in which more than two identical protein...
Support Vector Machine Proteins Databases, Protein Saccharomyces cerevisiae Saccharomyces cerevisiae Proteins Principal Component Analysis Area Under Curve Humans ROC Curve Protein Interaction Maps
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A computational method to predict topologically associating domain boundaries combining histone Marks and sequence information.

BMC genomics Dec 27, 2019
BACKGROUND: The three-dimensional (3D) structure of chromatins plays significant roles during cell differentiation and development. Hi-C and other 3C-based technologies allow us to look deep into the chromatin architectures. Many studies have suggest...
Histone Code Neural Networks, Computer Algorithms ROC Curve Histones Chromatin Protein Binding Area Under Curve
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iProDNA-CapsNet: identifying protein-DNA binding residues using capsule neural networks.

BMC bioinformatics Dec 27, 2019
BACKGROUND: Since protein-DNA interactions are highly essential to diverse biological events, accurately positioning the location of the DNA-binding residues is necessary. This biological issue, however, is currently a challenging task in the age of ...
Amino Acid Sequence Position-Specific Scoring Matrices DNA Amino Acids DNA-Binding Proteins Humans Neural Networks, Computer Reproducibility of Results ROC Curve Software Algorithms
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IILLS: predicting virus-receptor interactions based on similarity and semi-supervised learning.

BMC bioinformatics Dec 27, 2019
BACKGROUND: Viral infectious diseases are the serious threat for human health. The receptor-binding is the first step for the viral infection of hosts. To more effectively treat human viral infectious diseases, the hidden virus-receptor interactions ...
Humans Software Least-Squares Analysis Supervised Machine Learning Algorithms Viruses Reproducibility of Results Receptors, Virus ROC Curve
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Predicting breast cancer risk using personal health data and machine learning models.

PloS one Dec 27, 2019
Among women, breast cancer is a leading cause of death. Breast cancer risk predictions can inform screening and preventative actions. Previous works found that adding inputs to the widely-used Gail model improved its ability to predict breast cancer ...
Risk Assessment ROC Curve Health Records, Personal Aged Breast Neoplasms Middle Aged Humans Machine Learning Female
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Classification of adaptor proteins using recurrent neural networks and PSSM profiles.

BMC genomics Dec 24, 2019
BACKGROUND: Adaptor proteins are carrier proteins that play a crucial role in signal transduction. They commonly consist of several modular domains, each having its own binding activity and operating by forming complexes with other intracellular-sign...
Position-Specific Scoring Matrices Deep Learning ROC Curve Adaptor Proteins, Signal Transducing
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