Search results for "artificial"

showing 10 items of 7394 documents

2018

Despite major progress in Robotics and AI, robots are still basically "zombies" repeatedly achieving actions and tasks without understanding what they are doing. Deep-Learning AI programs classify tremendous amounts of data without grasping the meaning of their inputs or outputs. We still lack a genuine theory of the underlying principles and methods that would enable robots to understand their environment, to be cognizant of what they do, to take appropriate and timely initiatives, to learn from their own experience and to show that they know that they have learned and how. The rationale of this paper is that the understanding of its environment by an agent (the agent itself and its effect…

0301 basic medicinebusiness.industryComputer sciencemedia_common.quotation_subjectRoboticsCognitive architectureHuman–robot interactionComputer Science Applications03 medical and health sciences030104 developmental biology0302 clinical medicineArtificial IntelligenceHuman–computer interactionPerceptionSelf-awarenessRobotMeaning (existential)Artificial intelligenceAffordancebusiness030217 neurology & neurosurgerymedia_commonFrontiers in Robotics and AI
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Nature versus design: synthetic biology or how to build a biological non-machine.

2015

The engineering ideal of synthetic biology presupposes that organisms are composed of standard, interchangeable parts with a predictive behaviour. In one word, organisms are literally recognized as machines. Yet living objects are the result of evolutionary processes without any purposiveness, not of a design by external agents. Biological components show massive overlapping and functional degeneracy, standard-free complexity, intrinsic variation and context dependent performances. However, although organisms are not full-fledged machines, synthetic biologists may still be eager for machine-like behaviours from artificially modified biosystems.

0301 basic medicinebusiness.industrySystems biologySystems BiologyBiophysicsInterchangeable partsBioengineeringBiological evolutionBiologyBiochemistryBiological Evolutionlaw.invention03 medical and health sciencesSynthetic biology030104 developmental biologyMetabolic EngineeringlawEscherichia coliAnimalsHumansDegeneracy (biology)Synthetic BiologyArtificial intelligencebusinessBiotechnology
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Unraveling the Molecular Mechanism of Action of Empagliflozin in Heart Failure With Reduced Ejection Fraction With or Without Diabetes

2019

Visual Abstract

0301 basic medicinelcsh:Diseases of the circulatory (Cardiovascular) systemmedicine.medical_specialtyCardiac & Cardiovascular Systemsempagliflozinheart failure030204 cardiovascular system & hematologySGLT2i sodium-glucose co-transporter 2 inhibitorHF heart failurePRECLINICAL RESEARCH03 medical and health sciences0302 clinical medicineDM diabetes mellitusDiabetes mellitusInternal medicinemedicineEmpagliflozinMI-HF post-infarct heart failureGlycemicScience & TechnologyEjection fractionbusiness.industryNHE sodium-hydrogen exchangerANN artificial neural networkmedicine.diseaseHFrEF HF with reduced ejection fractionBlockadeXIAPmachine learning030104 developmental biologyMechanism of actionlcsh:RC666-701Heart failureCardiovascular System & CardiologyCardiologyRNAseq RNA sequencingempagtiflozinmedicine.symptomCardiology and Cardiovascular MedicinebusinessLife Sciences & BiomedicineJACC: Basic to Translational Science
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Unexpected associated microalgal diversity in the lichen Ramalina farinacea is uncovered by pyrosequencing analyses

2017

The current literature reveals that the intrathalline coexistence of multiple microalgal taxa in lichens is more common than previously thought, and additional complexity is supported by the coexistence of bacteria and basidiomycete yeasts in lichen thalli. This replaces the old paradigm that lichen symbiosis occurs between a fungus and a single photobiont. The lichen Ramalina farinacea has proven to be a suitable model to study the multiplicity of microalgae in lichen thalli due to the constant coexistence of Trebouxia sp. TR9 and T. jamesii in long-distance populations. To date, studies involving phycobiont diversity within entire thalli are based on Sanger sequencing, but this method see…

0301 basic medicinelcsh:MedicineLichenologyArtificial Gene Amplification and ExtensionPlant SciencePolymerase Chain ReactionDatabase and Informatics MethodsDiversity indexMicroalgaeCluster AnalysisDNA Fungallcsh:ScienceLichenPhylogenyData ManagementMultidisciplinaryEcologybiologyEcologyPhylogenetic AnalysisBiodiversitysymbiosisThallusPhylogeneticspyrosequencingLichenologyTrebouxiaSequence AnalysisResearch ArticleTrebouxiaComputer and Information SciencesBioinformaticsSequence DatabasesReal-Time Polymerase Chain ReactionResearch and Analysis MethodslichenRamalina farinacea03 medical and health sciencesAscomycotaAlgaelichen photobionts pyrosequencing symbiosis TrebouxiaBotanyEvolutionary SystematicsMolecular Biology TechniquesMolecular BiologyDNA sequence analysisTaxonomyEvolutionary BiologyEcology and Environmental Scienceslcsh:RGenetic VariationBiology and Life SciencesSequence Analysis DNAReverse Transcriptase-Polymerase Chain Reactionbiology.organism_classificationBiological Databases030104 developmental biologyphotobiontsPyrosequencinglcsh:QSequence AlignmentPLOS ONE
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Graphical Workflow System for Modification Calling by Machine Learning of Reverse Transcription Signatures

2019

Modification mapping from cDNA data has become a tremendously important approach in epitranscriptomics. So-called reverse transcription signatures in cDNA contain information on the position and nature of their causative RNA modifications. Data mining of, e.g. Illumina-based high-throughput sequencing data, is therefore fast growing in importance, and the field is still lacking effective tools. Here we present a versatile user-friendly graphical workflow system for modification calling based on machine learning. The workflow commences with a principal module for trimming, mapping, and postprocessing. The latter includes a quantification of mismatch and arrest rates with single-nucleotide re…

0301 basic medicinelcsh:QH426-470Downstream (software development)Computer scienceRT signatureMachine learningcomputer.software_genre[SDV.BBM.BM] Life Sciences [q-bio]/Biochemistry Molecular Biology/Molecular biologyField (computer science)m1A03 medical and health sciencesRNA modifications0302 clinical medicineEpitranscriptomics[SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry Molecular Biology/Genomics [q-bio.GN]GeneticsTechnology and CodeGalaxy platformGenetics (clinical)ComputingMilieux_MISCELLANEOUSbusiness.industryPrincipal (computer security)[SDV.BBM.BM]Life Sciences [q-bio]/Biochemistry Molecular Biology/Molecular biologyAutomationWatson–Crick faceVisualizationlcsh:Geneticsmachine learningComputingMethodologies_PATTERNRECOGNITION030104 developmental biologyWorkflow030220 oncology & carcinogenesisMolecular Medicine[SDV.BBM.GTP] Life Sciences [q-bio]/Biochemistry Molecular Biology/Genomics [q-bio.GN]TrimmingArtificial intelligencebusinesscomputer
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Taxonomic Classification for Living Organisms Using Convolutional Neural Networks

2017

Taxonomic classification has a wide-range of applications such as finding out more about evolutionary history. Compared to the estimated number of organisms that nature harbors, humanity does not have a thorough comprehension of to which specific classes they belong. The classification of living organisms can be done in many machine learning techniques. However, in this study, this is performed using convolutional neural networks. Moreover, a DNA encoding technique is incorporated in the algorithm to increase performance and avoid misclassifications. The algorithm proposed outperformed the state of the art algorithms in terms of accuracy and sensitivity, which illustrates a high potential f…

0301 basic medicinelcsh:QH426-470Taxonomic classificationADNCodificació Teoria de laBiologyBioinformaticsMachine learningcomputer.software_genreDNA; genes; taxonomic classification; convolutional neural networks; encodingConvolutional neural networkArticle03 medical and health sciences0302 clinical medicineBiologia -- ClassificacióEncoding (memory)convolutional neural networksGeneticstaxonomic classificationSensitivity (control systems)genesGenetics (clinical)ta113Biology -- Classificationbusiness.industryBiological classificationCoding theoryDNAencodinglcsh:Genetics030104 developmental biologyGenes030220 oncology & carcinogenesisEncodingConvolutional neural networksArtificial intelligenceCoding theorybusinesscomputerGens
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Review: the Use of Electromyography on Food Texture Assessment

2001

Sensory evaluation (SE) involves evoking, measuring and interpreting human responses to the properties of foods. Among these properties texture is an important one for food acceptability. Texture is mainly perceived through mastication, a process that changes food characteristics throughout time by comminuting and salivation. Electromyography (EMG) has emerged as a new tool in sensory evaluation mainly for assessing texture characteristics. Thus, it is interesting to analyze the knowledge so far generated and the procedures employed. Bipolar surface electrodes are placed on the four main masticatory muscles (masseter right-left and temporalis right-left) and their electric activity recorded…

0301 basic medicinemedicine.diagnostic_testbusiness.industryGeneral Chemical EngineeringPattern recognition030206 dentistryElectromyographyTexture (music)Industrial and Manufacturing EngineeringMasticatory force03 medical and health sciences030104 developmental biology0302 clinical medicineCrunchinessFood texturemedicineCooked meatArtificial intelligencebusinessMasticationFood ScienceMathematicsFood Science and Technology International
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Machine learning–XGBoost analysis of language networks to classify patients with epilepsy

2017

Our goal was to apply a statistical approach to allow the identification of atypical language patterns and to differentiate patients with epilepsy from healthy subjects, based on their cerebral activity, as assessed by functional MRI (fMRI). Patients with focal epilepsy show reorganization or plasticity of brain networks involved in cognitive functions, inducing ‘atypical’ (compared to ‘typical’ in healthy people) brain profiles. Moreover, some of these patients suffer from drug-resistant epilepsy, and they undergo surgery to stop seizures. The neurosurgeon should only remove the zone generating seizures and must preserve cognitive functions to avoid deficits. To preserve functions, one sho…

0301 basic medicinemedicine.medical_specialtyCognitive Neuroscience[SCCO.COMP]Cognitive science/Computer scienceAudiologyExtreme Gradient Boostinglcsh:Computer applications to medicine. Medical informaticsArticle03 medical and health sciencesEpilepsy0302 clinical medicineText miningMachine learningmedicineLanguagelcsh:Computer softwareEpilepsyCognitive mapReceiver operating characteristicbusiness.industryCognitionNeurophysiologymedicine.diseaseMLComputer Science ApplicationsStatistical classificationlcsh:QA76.75-76.765030104 developmental biologyNeurologyBinary classification[ SCCO.COMP ] Cognitive science/Computer sciencelcsh:R858-859.7Artificial intelligencePsychologybusiness030217 neurology & neurosurgeryAtypicalXGBoost
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Automatic detection and measurement of nuchal translucency.

2017

In this paper we propose a new methodology to support the physician both to identify automatically the nuchal region and to obtain a correct thickness measurement of the nuchal translucency. The thickness of the nuchal translucency is one of the main markers for screening of chromosomal defects such as trisomy 13, 18 and 21. Its measurement is performed during ultrasound scanning in the first trimester of pregnancy. The proposed methodology is mainly based on wavelet and multi resolution analysis. The performance of our method was analysed on 382 random frames, representing mid-sagittal sections, uniformly extracted from real clinical ultrasound videos of 12 patients. According to the groun…

0301 basic medicinemedicine.medical_specialtyWavelet AnalysisFirst trimester of pregnancyHealth InformaticsSensitivity and SpecificityWavelet analysi030218 nuclear medicine & medical imagingPattern Recognition AutomatedMachine Learning03 medical and health sciencesPrenatal ultrasound0302 clinical medicineNuchal regionNuchal translucencyUltrasound fetal examinationMedian sagittal sectionNuchal Translucency MeasurementImage Interpretation Computer-AssistedMedicineHumansPixelbusiness.industryMulti resolution analysisUltrasoundReproducibility of ResultsPattern recognitionComputer Science Applications1707 Computer Vision and Pattern RecognitionComputer Science ApplicationsSurgeryClinical ultrasound030104 developmental biologyNuchal translucencyArtificial intelligenceDown SyndromebusinessNuchal Translucency MeasurementAlgorithmsComputers in biology and medicine
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Multivariate statistical analysis of a large odorants database aimed at revealing similarities and links between odorants and odors

2017

International audience; The perception of odor is an important component of smell; the first step of odor detection, and the discrimination of structurally diverse odorants depends on their interactions with olfactory receptors (ORs). Indeed, the perception of an odor's quality results from a combinatorial coding, in which the deciphering remains a major challenge. Several studies have successfully established links between odors and odorants by categorizing and classifying data. Hence, the categorization of odors appears to be a promising way to manage odors. In the proposed study, we performed a computational analysis using odor descriptions of the odorants present in Flavor-Base 9th Edit…

0301 basic medicinemultidimensional scalingmedia_common.quotation_subjectAgglomerative hierarchical clusteringKohonen self-organizing mapsodorants03 medical and health sciences0302 clinical medicinePerceptionComputational analysisMultidimensional scalingmedia_commonChemistrybusiness.industrymusculoskeletal neural and ocular physiologyPattern recognitionKohonen self organizing mapGeneral Chemistrycategorization030104 developmental biologyCategorizationOdorodor notesagglomerative hierarchical clusteringArtificial intelligenceMultivariate statisticalbusiness[SDV.AEN]Life Sciences [q-bio]/Food and Nutrition030217 neurology & neurosurgerypsychological phenomena and processesFood Science
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