AIMC Topic: Datasets as Topic

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m6A-Atlas: a comprehensive knowledgebase for unraveling the N6-methyladenosine (m6A) epitranscriptome.

Nucleic acids research Jan 8, 2021
N 6-Methyladenosine (m6A) is the most prevalent RNA modification on mRNAs and lncRNAs. It plays a pivotal role during various biological processes and disease pathogenesis. We present here a comprehensive knowledgebase, m6A-Atlas, for unraveling the ...
Dengue Virus HIV Zebrafish Knowledge Bases RNA, Messenger Rats MicroRNAs RNA, Long Noncoding Adenosine Atlases as Topic Arabidopsis Pan troglodytes Datasets as Topic Saccharomyces cerevisiae Drosophila melanogaster Herpesvirus 8, Human Humans Animals Swine Transcriptome Mice
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Epistasis Analysis: Classification Through Machine Learning Methods.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2021
Complex disease is different from Mendelian disorders. Its development usually involves the interaction of multiple genes or the interaction between genes and the environment (i.e. epistasis). Although the high-throughput sequencing technologies for ...
Humans Machine Learning Software Polymorphism, Single Nucleotide Computational Biology Models, Genetic Datasets as Topic Epistasis, Genetic Multifactor Dimensionality Reduction Multifactorial Inheritance
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Epistasis Detection Based on Epi-GTBN.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2021
Epistasis detection is a hot topic in bioinformatics due to its relevance to the detection of specific phenotypic traits and gene-gene interactions. Here, we present a step-by-step protocol to apply Epi-GTBN, a machine learning-based method based on ...
Polymorphism, Single Nucleotide Genotype Models, Genetic Bayes Theorem Machine Learning Humans Genetic Loci Software Data Mining Phenotype Datasets as Topic Gene Regulatory Networks Epistasis, Genetic
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A Belief Degree-Associated Fuzzy Multifactor Dimensionality Reduction Framework for Epistasis Detection.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2021
Epistasis is a challenge in prediction, classification, and suspicion of human genetic diseases. Many technologies, methods, and tools have been developed for epistasis detection. Multifactor dimensionality reduction (MDR) is the method commonly used...
Datasets as Topic Epistasis, Genetic Uncertainty Multifactor Dimensionality Reduction Multifactorial Inheritance Models, Genetic Databases, Genetic Fuzzy Logic Coronary Artery Disease Humans Software Algorithms Polymorphism, Single Nucleotide
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Deep Neural Networks for Epistatic Sequence Analysis.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2021
We report a step-by-step protocol to use pysster, a TensorFlow-based package for building deep neural networks on a broad range of epistatic sequences such as DNA, RNA, or annotated secondary structure sequences. Pysster provides users comprehensive ...
Base Sequence Epistasis, Genetic Sequence Analysis RNA Editing ROC Curve Models, Genetic RNA Datasets as Topic Humans Software Deep Learning
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Ten computer codes that transformed science.

Nature Jan 1, 2021
Time Factors Computational Biology United States Databases, Protein Neural Networks, Computer Algorithms Databases, Factual Deep Learning Physics National Library of Medicine (U.S.) National Institutes of Health (U.S.) Preprints as Topic History, 20th Century Databases, Nucleic Acid Weather Fourier Analysis Programming Languages Datasets as Topic History, 21st Century
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Adversarial attack on deep learning-based dermatoscopic image recognition systems: Risk of misdiagnosis due to undetectable image perturbations.

Medicine Dec 11, 2020
Deep learning algorithms have shown excellent performances in the field of medical image recognition, and practical applications have been made in several medical domains. Little is known about the feasibility and impact of an undetectable adversaria...
Skin Diseases Humans Image Interpretation, Computer-Assisted Neural Networks, Computer Diagnostic Errors Datasets as Topic Deep Learning Algorithms Models, Statistical Reproducibility of Results Skin Risk Factors Sensitivity and Specificity
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Clinical concept extraction using transformers.

Journal of the American Medical Informatics Association : JAMIA Dec 9, 2020
OBJECTIVE: The goal of this study is to explore transformer-based models (eg, Bidirectional Encoder Representations from Transformers [BERT]) for clinical concept extraction and develop an open-source package with pretrained clinical models to facili...
Data Mining Datasets as Topic Humans Software Electronic Health Records Deep Learning Natural Language Processing
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Probabilistic forecasting of surgical case duration using machine learning: model development and validation.

Journal of the American Medical Informatics Association : JAMIA Dec 9, 2020
OBJECTIVE: Accurate estimations of surgical case durations can lead to the cost-effective utilization of operating rooms. We developed a novel machine learning approach, using both structured and unstructured features as input, to predict a continuou...
Operating Rooms Models, Statistical Humans Natural Language Processing Machine Learning Neural Networks, Computer Datasets as Topic Forecasting Surgical Procedures, Operative Reproducibility of Results Operative Time
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Potential of Artificial Intelligence for Estimating Japanese Fetal Weights.

Acta medica Okayama Dec 1, 2020
We developed an artificial intelligence (AI) method for estimating fetal weights of Japanese fetuses based on the gestational weeks and the bi-parietal diameter, abdominal circumference, and femur length. The AI comprised of neural network architectu...
Gestational Age Deep Learning Humans Asian People Fetal Weight Pregnancy Japan Datasets as Topic Female Ultrasonography, Prenatal
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