AIMC Topic: Terminology as Topic

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A network-based machine-learning framework to identify both functional modules and disease genes.

Human genetics Jan 7, 2021
Disease gene identification is a critical step towards uncovering the molecular mechanisms of diseases and systematically investigating complex disease phenotypes. Despite considerable efforts to develop powerful computing methods, candidate gene ide...
Humans Mental Disorders Predictive Value of Tests Metabolic Networks and Pathways Neurodegenerative Diseases Supervised Machine Learning Neoplasms Gene Regulatory Networks Computational Biology Amino Acid Sequence Musculoskeletal Diseases Protein Interaction Mapping Metabolic Diseases Immune System Diseases Terminology as Topic Gastrointestinal Diseases
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Learning and interpreting the gene regulatory grammar in a deep learning framework.

PLoS computational biology Nov 2, 2020
Deep neural networks (DNNs) have achieved state-of-the-art performance in identifying gene regulatory sequences, but they have provided limited insight into the biology of regulatory elements due to the difficulty of interpreting the complex features...
Neural Networks, Computer Computer Simulation Databases, Genetic Terminology as Topic Binding Sites Enhancer Elements, Genetic Genes, Regulator Mice Computational Biology Animals Models, Genetic Transcription Factors Deep Learning Gene Regulatory Networks
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[Explore the history of artificial intelligence, to better define and understand it].

Medecine sciences : M/S Oct 7, 2020
History, 20th Century Delivery of Health Care Biomedical Research History, 21st Century Terminology as Topic Humans Artificial Intelligence
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LncLocation: Efficient Subcellular Location Prediction of Long Non-Coding RNA-Based Multi-Source Heterogeneous Feature Fusion.

International journal of molecular sciences Oct 1, 2020
Recent studies uncover that subcellular location of long non-coding RNAs (lncRNAs) can provide significant information on its function. Due to the lack of experimental data, the number of lncRNAs is very limited, experimentally verified subcellular l...
Datasets as Topic Cell Nucleus Gene Expression Regulation Base Sequence RNA, Long Noncoding Benchmarking Exosomes Ribosomes Eukaryotic Cells Genome, Human Terminology as Topic Cytoplasm Humans Software Support Vector Machine Databases, Genetic Animals Computational Biology
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One Algorithm May Not Fit All: How Selection Bias Affects Machine Learning Performance.

Radiographics : a review publication of the Radiological Society of North America, Inc Sep 25, 2020
Machine learning (ML) algorithms have demonstrated high diagnostic accuracy in identifying and categorizing disease on radiologic images. Despite the results of initial research studies that report ML algorithm diagnostic accuracy similar to or excee...
Selection Bias Humans Terminology as Topic Machine Learning Diagnostic Imaging
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Ontology and values anchor indigenous and grey nomenclatures: a case study in lichen naming practices among the Samí, Sherpa, Scots, and Okanagan.

Studies in history and philosophy of biological and biomedical sciences Sep 10, 2020
Ethnobotanical research provides ample justification for comparing diverse biological nomenclatures and exploring ways that retain alternative naming practices. However, how (and whether) comparison of nomenclatures is possible remains a subject of d...
Nepal Terminology as Topic Norway Lichens Population Groups British Columbia Humans Scotland Social Values Biological Ontologies
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Detecting modeling inconsistencies in SNOMED CT using a machine learning technique.

Methods (San Diego, Calif.) May 20, 2020
SNOMED CT is a comprehensive and evolving clinical reference terminology that has been widely adopted as a common vocabulary to promote interoperability between Electronic Health Records. Owing to its importance in healthcare, quality assurance becom...
Machine Learning Electronic Health Records Quality Control Systematized Nomenclature of Medicine Terminology as Topic Medical Informatics Semantics
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Analysis of gene expression profiles of lung cancer subtypes with machine learning algorithms.

Biochimica et biophysica acta. Molecular basis of disease Apr 28, 2020
Lung cancer is one of the most common cancer types worldwide and causes more than one million deaths annually. Lung adenocarcinoma (AC) and lung squamous cell cancer (SCC) are two major lung cancer subtypes and have different characteristics in sever...
Monte Carlo Method Serpins Adenocarcinoma of Lung Cystatin A Adenosine Triphosphatases Carcinoma, Squamous Cell Terminology as Topic Gene Expression Profiling Membrane Transport Proteins Transcriptome Diagnosis, Differential Computational Biology Lung Neoplasms Humans Cadherins Datasets as Topic Gene Expression Regulation, Neoplastic Machine Learning Transcription Factors Tumor Suppressor Proteins
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FHIR OWL: Transforming OWL ontologies into FHIR terminology resources.

AMIA ... Annual Symposium proceedings. AMIA Symposium Mar 4, 2020
The FHIR specification provides a mechanism to access clinical terminologies using a standard API, and many existing terminologies, such as SNOMED CT, are well supported. However, in areas such as genomics, terminologies from other domains are starti...
Humans Health Information Interoperability Genomics Terminology as Topic Biological Ontologies Vocabulary, Controlled
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genoDraw: A Web Tool for Developing Pedigree Diagrams Using the Standardized Human Pedigree Nomenclature Integrated with Biomedical Vocabularies.

AMIA ... Annual Symposium proceedings. AMIA Symposium Mar 4, 2020
The integration of genetic information in current clinical routine has raised a need for tools to exploit family genetic knowledge. On the clinical side, an application for managing and visualizing pedigree diagrams could provide genetics specialists...
Humans Vocabulary, Controlled Computer Graphics Software Biological Ontologies Pedigree Internet Terminology as Topic
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