AIMC Topic:
Supervised Machine Learning

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TAGOOS: genome-wide supervised learning of non-coding loci associated to complex phenotypes.

Nucleic acids research Aug 22, 2019
Genome-wide association studies (GWAS) associate single nucleotide polymorphisms (SNPs) to complex phenotypes. Most human SNPs fall in non-coding regions and are likely regulatory SNPs, but linkage disequilibrium (LD) blocks make it difficult to dist...
Genetic Predisposition to Disease Polymorphism, Single Nucleotide Computational Biology Humans Phenotype Genome-Wide Association Study Quantitative Trait Loci Linkage Disequilibrium Regulatory Sequences, Nucleic Acid Internet Supervised Machine Learning Gene Expression Regulation
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A New Approach to Compare the Performance of Two Classification Methods of Causes of Death for Timely Surveillance in France.

Studies in health technology and informatics Aug 21, 2019
Timely mortality surveillance in France is based on the monitoring of electronic death certificates to provide information to health authorities. This study aims to analyze the performance of a rule-based and a supervised machine learning method to c...
Humans Health Resources Death Certificates Cause of Death Supervised Machine Learning France
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Deciphering complex metabolite mixtures by unsupervised and supervised substructure discovery and semi-automated annotation from MS/MS spectra.

Faraday discussions Aug 15, 2019
Complex metabolite mixtures are challenging to unravel. Mass spectrometry (MS) is a widely used and sensitive technique for obtaining structural information of complex mixtures. However, just knowing the molecular masses of the mixture's constituents...
Databases, Factual Unsupervised Machine Learning Supervised Machine Learning Tandem Mass Spectrometry Automation Complex Mixtures
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Validation of a Cyclic Algorithm to Proxy Number of Lines of Systemic Cancer Therapy Using Administrative Data.

JCO clinical cancer informatics Aug 1, 2019
PURPOSE: Researchers are automating the process for identifying the number of lines of systemic cancer therapy received by patients. To date, algorithm development has involved manual modifications to predefined classification rules. In this study, w...
Humans Algorithms Antineoplastic Combined Chemotherapy Protocols Research Design Registries Supervised Machine Learning Neoplasms
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Impact of Artificial Intelligence on Interventional Cardiology: From Decision-Making Aid to Advanced Interventional Procedure Assistance.

JACC. Cardiovascular interventions Jul 22, 2019
Access to big data analyzed by supercomputers using advanced mathematical algorithms (i.e., deep machine learning) has allowed for enhancement of cognitive output (i.e., visual imaging interpretation) to previously unseen levels and promises to funda...
Cardiac Catheterization Humans Machine Learning Decision Support Techniques Robotics Deep Learning Workflow Patient Selection Unsupervised Machine Learning Supervised Machine Learning Clinical Decision-Making Diffusion of Innovation Predictive Value of Tests Cardiovascular Diseases Therapy, Computer-Assisted Diagnosis, Computer-Assisted
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Semi-Supervised Learning for Low-Dose CT Image Restoration with Hierarchical Deep Generative Adversarial Network (HD-GAN).

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
In the absence of duplicate high-dose CT data, it is challenging to restore high-quality images based on deep learning with only low-dose CT (LDCT) data. When different reconstruction algorithms and settings are adopted to prepare high-quality images...
Deep Learning Humans Image Processing, Computer-Assisted Algorithms Supervised Machine Learning Tomography, X-Ray Computed
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Boundary-aware Semi-supervised Deep Learning for Breast Ultrasound Computer-Aided Diagnosis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Breast ultrasound (US) is an effective imaging modality for breast cancer diagnosis. US computer-aided diagnosis (CAD) systems have been developed for decades and have employed either conventional handcrafted features or modern automatic deep-learned...
Image Processing, Computer-Assisted Ultrasonography, Mammary Supervised Machine Learning Breast Neoplasms Diagnosis, Computer-Assisted Deep Learning Humans Female
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Deep learning: new computational modelling techniques for genomics.

Nature reviews. Genetics Jul 1, 2019
As a data-driven science, genomics largely utilizes machine learning to capture dependencies in data and derive novel biological hypotheses. However, the ability to extract new insights from the exponentially increasing volume of genomics data requir...
Genomics Neural Networks, Computer Computer Simulation Deep Learning Humans Supervised Machine Learning Base Sequence Models, Genetic Unsupervised Machine Learning
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Semi-supervised learning of Hidden Markov Models for biological sequence analysis.

Bioinformatics (Oxford, England) Jul 1, 2019
MOTIVATION: Hidden Markov Models (HMMs) are probabilistic models widely used in applications in computational sequence analysis. HMMs are basically unsupervised models. However, in the most important applications, they are trained in a supervised man...
Sequence Analysis Models, Statistical Supervised Machine Learning Markov Chains Algorithms
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SuperCT: a supervised-learning framework for enhanced characterization of single-cell transcriptomic profiles.

Nucleic acids research May 7, 2019
Characterization of individual cell types is fundamental to the study of multicellular samples. Single-cell RNAseq techniques, which allow high-throughput expression profiling of individual cells, have significantly advanced our ability of this task....
Datasets as Topic Single-Cell Analysis Cell Lineage Animals Gene Expression Regulation, Neoplastic Mice Supervised Machine Learning RNA, Small Cytoplasmic Gene Expression Profiling Sequence Analysis, RNA Cluster Analysis Transcriptome Humans High-Throughput Nucleotide Sequencing Pancreatic Neoplasms Software
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