Výsledky vyhľadávania - computing algorithms and (((bioinformation OR informatika) OR informatika) OR informatics)

Replacing non-biomedical concepts improves embedding of biomedical concepts

Autori: Niyonkuru, Enock Gomez, Mauricio Soto Casarighi, Elena a ďalší

Zdroj: PLOS ONE. 20(5)

Predmety: Information and Computing Sciences, Biological Sciences, Bioinformatics and Computational Biology, Algorithms, Machine Learning, Semantics, Medical Informatics Computing, General Science & Technology

Popis súboru: application/pdf

Prístupová URL adresa: https://escholarship.org/uc/item/43k9s6k4
https://escholarship.org/content/qt43k9s6k4/qt43k9s6k4.pdf

Automated and flexible identification of complex disease: building a model for systemic lupus erythematosus using noisy labeling

Autori: Murray, Sara G Avati, Anand Schmajuk, Gabriela a ďalší

Zdroj: Journal of the American Medical Informatics Association. 26(1)

Predmety: 46 Information and Computing Sciences (for-2020), 4611 Machine Learning (for-2020), Patient Safety (rcdc), Lupus (rcdc), Networking and Information Technology R&D (NITRD) (rcdc), Machine Learning and Artificial Intelligence (rcdc), Autoimmune Disease (rcdc), Inflammatory and immune system (hrcs-hc), 3 Good Health and Well Being (sdg), Algorithms (mesh), Electronic Health Records (mesh), Humans (mesh), Lupus Erythematosus, Systemic (mesh), Machine Learning (mesh), ROC Curve (mesh), electronic health records, machine learning, lupus erythematosus, EHR phenotyping, EHR algorithms, Humans (mesh), Lupus Erythematosus, Systemic (mesh), ROC Curve (mesh), Algorithms (mesh), Electronic Health Records (mesh), Machine Learning (mesh), Algorithms (mesh), Electronic Health Records (mesh), Humans (mesh), Lupus Erythematosus, Systemic (mesh), Machine Learning (mesh), ROC Curve (mesh), 08 Information and Computing Sciences (for), 09 Engineering (for), 11 Medical and Health Sciences (for), Medical Informatics (science-metrix), 32 Biomedical and clinical sciences (for-2020), 42 Health sciences (for-2020), 46 Information and computing sciences (for-2020)

Popis súboru: application/pdf

Prístupová URL adresa: https://escholarship.org/uc/item/22f2m6v4
https://escholarship.org/content/qt22f2m6v4/qt22f2m6v4.pdf

BioSimulator.jl: Stochastic simulation in Julia

Autori: Landeros, Alfonso Stutz, Timothy Keys, Kevin L a ďalší

Zdroj: Computer Methods and Programs in Biomedicine. 167

Predmety: 46 Information and Computing Sciences (for-2020), 4601 Applied Computing (for-2020), Bioengineering (rcdc), Algorithms (mesh), Computer Simulation (mesh), Kinetics (mesh), Markov Chains (mesh), Models, Biological (mesh), Poisson Distribution (mesh), Probability (mesh), Programming Languages (mesh), Software (mesh), Stochastic Processes (mesh), Systems Biology (mesh), Stochastic simulation, Gillespie algorithm, tau-leaping, Systems biology, Julia language, Probability (mesh), Markov Chains (mesh), Poisson Distribution (mesh), Stochastic Processes (mesh), Systems Biology (mesh), Kinetics (mesh), Algorithms (mesh), Models, Biological (mesh), Computer Simulation (mesh), Software (mesh), Programming Languages (mesh), Gillespie algorithm, Julia language, Stochastic simulation, Systems biology, τ-leaping, Algorithms (mesh), Computer Simulation (mesh), Kinetics (mesh), Markov Chains (mesh), Models, Biological (mesh), Poisson Distribution (mesh), Probability (mesh), Programming Languages (mesh), Software (mesh), Stochastic Processes (mesh), Systems Biology (mesh), q-bio.QM, q-bio.QM, math.DS, 0801 Artificial Intelligence and Image Processing (for), 0903 Biomedical Engineering (for), 0906 Electrical and Electronic Engineering (for), Medical Informatics (science-metrix), 4003 Biomedical engineering (for-2020), 4601 Applied computing (for-2020), 4603 Computer vision and multimedia computation (for-2020)

Popis súboru: application/pdf

Prístupová URL adresa: https://escholarship.org/uc/item/62r288hd
https://escholarship.org/content/qt62r288hd/qt62r288hd.pdf

Using insurance claims to predict and improve hospitalizations and biologics use in members with inflammatory bowel diseases

Autori: Vaughn, Don A van Deen, Welmoed K Kerr, Wesley T a ďalší

Zdroj: Journal of Biomedical Informatics. 81

Predmety: 4203 Health Services and Systems (for-2020), 42 Health Sciences (for-2020), Crohn's Disease (rcdc), Inflammatory Bowel Disease (rcdc), Digestive Diseases (rcdc), Precision Medicine (rcdc), Autoimmune Disease (rcdc), Oral and gastrointestinal (hrcs-hc), 3 Good Health and Well Being (sdg), Adult (mesh), Algorithms (mesh), Area Under Curve (mesh), Biological Products (mesh), Colitis, Ulcerative (mesh), Crohn Disease (mesh), Data Collection (mesh), Databases, Factual (mesh), Decision Making (mesh), Health Care Costs (mesh), Hospitalization (mesh), Humans (mesh), Insurance Claim Review (mesh), Insurance, Health (mesh), International Classification of Diseases (mesh), Models, Theoretical (mesh), Pattern Recognition, Automated (mesh), Predictive Value of Tests (mesh), Quality of Life (mesh), Regression Analysis (mesh), Treatment Outcome (mesh), Insurance claims, Prediction, Inflammatory bowel disease, Hospitalization, Biologics, Topic modeling, Humans (mesh), Colitis, Ulcerative (mesh), Crohn Disease (mesh), Biological Products (mesh), Treatment Outcome (mesh), Hospitalization (mesh), Data Collection (mesh), Area Under Curve (mesh), Regression Analysis (mesh), Predictive Value of Tests (mesh), Decision Making (mesh), Algorithms (mesh), Models, Theoretical (mesh), Quality of Life (mesh), International Classification of Diseases (mesh), Databases, Factual (mesh), Pattern Recognition, Automated (mesh), Adult (mesh), Health Care Costs (mesh), Insurance Claim Review (mesh), Insurance, Health (mesh), Biologics, Hospitalization, Inflammatory bowel disease, Insurance claims, Prediction, Topic modeling, Adult (mesh), Algorithms (mesh), Area Under Curve (mesh), Biological Products (mesh), Colitis, Ulcerative (mesh), Crohn Disease (mesh), Data Collection (mesh), Databases, Factual (mesh), Decision Making (mesh), Health Care Costs (mesh), Hospitalization (mesh), Humans (mesh), Insurance Claim Review (mesh), Insurance, Health (mesh), International Classification of Diseases (mesh), Models, Theoretical (mesh), Pattern Recognition, Automated (mesh), Predictive Value of Tests (mesh), Quality of Life (mesh), Regression Analysis (mesh), Treatment Outcome (mesh), Insurance claims, prediction, inflammatory bowel disease, hospitalization, biologics, topic modeling, 06 Biological Sciences (for), 08 Information and Computing Sciences (for), 11 Medical and Health Sciences (for), Biomedical Engineering (science-metrix), Medical Informatics (science-metrix), 4203 Health services and systems (for-2020), 4601 Applied computing (for-2020)

Prístupová URL adresa: https://escholarship.org/uc/item/3jk7c5rg

Creation of a Robust and Generalizable Machine Learning Classifier for Patient Ventilator Asynchrony*

Autori: Rehm, Gregory B Han, Jinyoung Kuhn, Brooks T a ďalší

Zdroj: Methods of Information in Medicine. 57(04)

Predmety: 46 Information and Computing Sciences (for-2020), 42 Health Sciences (for-2020), 4611 Machine Learning (for-2020), Networking and Information Technology R&D (NITRD) (rcdc), Machine Learning and Artificial Intelligence (rcdc), Patient Safety (rcdc), Bioengineering (rcdc), Algorithms (mesh), Decision Support Systems, Clinical (mesh), Humans (mesh), Machine Learning (mesh), Models, Theoretical (mesh), Respiration (mesh), Respiration, Artificial (mesh), Time Factors (mesh), Patient ventilator asynchrony, artificial respiration, machine learning, intensive care units, clinical decision support systems, Humans (mesh), Respiration, Artificial (mesh), Respiration (mesh), Algorithms (mesh), Models, Theoretical (mesh), Time Factors (mesh), Decision Support Systems, Clinical (mesh), Machine Learning (mesh), Algorithms (mesh), Decision Support Systems, Clinical (mesh), Humans (mesh), Machine Learning (mesh), Models, Theoretical (mesh), Respiration (mesh), Respiration, Artificial (mesh), Time Factors (mesh), 06 Biological Sciences (for), 08 Information and Computing Sciences (for), 11 Medical and Health Sciences (for), Medical Informatics (science-metrix), 31 Biological sciences (for-2020), 42 Health sciences (for-2020), 46 Information and computing sciences (for-2020)

Popis súboru: application/pdf

Prístupová URL adresa: https://escholarship.org/uc/item/2bs678wt
https://escholarship.org/content/qt2bs678wt/qt2bs678wt.pdf

Learning from healthy and stable eyes: A new approach for detection of glaucomatous progression

Autori: Belghith, Akram Bowd, Christopher Medeiros, Felipe A a ďalší

Zdroj: Artificial Intelligence in Medicine. 64(2)

Predmety: 46 Information and Computing Sciences (for-2020), 32 Biomedical and Clinical Sciences (for-2020), 4603 Computer Vision and Multimedia Computation (for-2020), 3212 Ophthalmology and Optometry (for-2020), Bioengineering (rcdc), Aging (rcdc), Biomedical Imaging (rcdc), Neurodegenerative (rcdc), Neurosciences (rcdc), Eye Disease and Disorders of Vision (rcdc), Clinical Research (rcdc), 4.2 Evaluation of markers and technologies (hrcs-rac), 4.1 Discovery and preclinical testing of markers and technologies (hrcs-rac), Eye (hrcs-hc), Algorithms (mesh), Bayes Theorem (mesh), Computer Simulation (mesh), Decision Support Systems, Clinical (mesh), Decision Support Techniques (mesh), Disease Progression (mesh), Eye (mesh), Glaucoma (mesh), Humans (mesh), Image Interpretation, Computer-Assisted (mesh), Imaging, Three-Dimensional (mesh), Models, Statistical (mesh), Predictive Value of Tests (mesh), Reproducibility of Results (mesh), Time Factors (mesh), Tomography, Optical Coherence (mesh), Spatial dependency modeling, Copula theory, Kernel classifier, Glaucoma progression detection, Eye (mesh), Humans (mesh), Glaucoma (mesh), Disease Progression (mesh), Image Interpretation, Computer-Assisted (mesh), Imaging, Three-Dimensional (mesh), Tomography, Optical Coherence (mesh), Models, Statistical (mesh), Bayes Theorem (mesh), Reproducibility of Results (mesh), Predictive Value of Tests (mesh), Algorithms (mesh), Decision Support Techniques (mesh), Time Factors (mesh), Computer Simulation (mesh), Decision Support Systems, Clinical (mesh), Copula theory, Glaucoma progression detection, Kernel classifier, Spatial dependency modeling, Algorithms (mesh), Bayes Theorem (mesh), Computer Simulation (mesh), Decision Support Systems, Clinical (mesh), Decision Support Techniques (mesh), Disease Progression (mesh), Eye (mesh), Glaucoma (mesh), Humans (mesh), Image Interpretation, Computer-Assisted (mesh), Imaging, Three-Dimensional (mesh), Models, Statistical (mesh), Predictive Value of Tests (mesh), Reproducibility of Results (mesh), Time Factors (mesh), Tomography, Optical Coherence (mesh), 08 Information and Computing Sciences (for), 09 Engineering (for), Medical Informatics (science-metrix), 32 Biomedical and clinical sciences (for-2020), 42 Health sciences (for-2020), 46 Information and computing sciences (for-2020)

Prístupová URL adresa: https://escholarship.org/uc/item/59d93274

Bandwidth vs BFS Width in Matrix Reordering, Graph Reconstruction, and Graph Drawing

Autori: Eppstein, D Goodrich, MT Liu, S

Zdroj: Leibniz International Proceedings in Informatics Lipics. 351

Predmety: 46 Information and computing sciences (for-2020)

Prístupová URL adresa: https://escholarship.org/uc/item/35q5x6tf

A Risk-Based Clinical Decision Support System for Patient-Specific Antimicrobial Therapy (iBiogram): Design and Retrospective Analysis

Autori: Müller, Lars Srinivasan, Aditya Abeles, Shira R a ďalší

Zdroj: Journal of Medical Internet Research. 23(12)

Predmety: 4203 Health Services and Systems (for-2020), 42 Health Sciences (for-2020), Infectious Diseases (rcdc), Networking and Information Technology R&D (NITRD) (rcdc), Emerging Infectious Diseases (rcdc), Patient Safety (rcdc), Clinical Research (rcdc), 7.3 Management and decision making (hrcs-rac), Infection (hrcs-hc), 3 Good Health and Well Being (sdg), Anti-Bacterial Agents (mesh), Anti-Infective Agents (mesh), Decision Support Systems, Clinical (mesh), Humans (mesh), Retrospective Studies (mesh), antimicrobial resistance, clinical decision support, antibiotic stewardship, data visualization, Humans (mesh), Anti-Infective Agents (mesh), Anti-Bacterial Agents (mesh), Retrospective Studies (mesh), Decision Support Systems, Clinical (mesh), antibiotic stewardship, antimicrobial resistance, clinical decision support, data visualization, Anti-Bacterial Agents (mesh), Anti-Infective Agents (mesh), Decision Support Systems, Clinical (mesh), Humans (mesh), Retrospective Studies (mesh), 08 Information and Computing Sciences (for), 11 Medical and Health Sciences (for), 17 Psychology and Cognitive Sciences (for), Medical Informatics (science-metrix), 4203 Health services and systems (for-2020)

Popis súboru: application/pdf

Prístupová URL adresa: https://escholarship.org/uc/item/0s2898wm
https://escholarship.org/content/qt0s2898wm/qt0s2898wm.pdf

Computational Geometry with Probabilistically Noisy Primitive Operations

Autori: Eppstein, D Goodrich, MT Sridhar, V

Zdroj: Leibniz International Proceedings in Informatics Lipics. 349

Predmety: 46 Information and computing sciences (for-2020)

Prístupová URL adresa: https://escholarship.org/uc/item/2z8632j4

Sampling Conditions for Conforming Voronoi Meshing by the VoroCrust Algorithm

Autori: Abdelkader, Ahmed Bajaj, Chandrajit L Ebeida, Mohamed S a ďalší

Zdroj: LIPIcs : Leibniz international proceedings in informatics. 99

Predmety: Information and Computing Sciences, Graphics, Augmented Reality and Games, Voronoi, polyhedral meshing, sampling conditions, surface reconstruction, cs.CG, I.3.5, Information and computing sciences

Popis súboru: application/pdf

Prístupová URL adresa: https://escholarship.org/uc/item/43r7q64x
https://escholarship.org/content/qt43r7q64x/qt43r7q64x.pdf

Saliency-driven system models for cell analysis with deep learning

Autori: Ferreira, Daniel S Ramalho, Geraldo LB Torres, Débora a ďalší

Zdroj: Computer Methods and Programs in Biomedicine. 182

Predmety: 46 Information and Computing Sciences (for-2020), 4611 Machine Learning (for-2020), Eye Disease and Disorders of Vision (rcdc), Bioengineering (rcdc), Networking and Information Technology R&D (NITRD) (rcdc), Machine Learning and Artificial Intelligence (rcdc), Cervix Uteri (mesh), Deep Learning (mesh), Female (mesh), Humans (mesh), Neural Networks, Computer (mesh), Papanicolaou Test (mesh), Saliency prediction, Convolutional neural network, Cell analysis, Eye tracking experiment, Cervix Uteri (mesh), Humans (mesh), Female (mesh), Papanicolaou Test (mesh), Deep Learning (mesh), Neural Networks, Computer (mesh), Cell analysis, Convolutional neural network, Eye tracking experiment, Saliency prediction, Cervix Uteri (mesh), Deep Learning (mesh), Female (mesh), Humans (mesh), Neural Networks, Computer (mesh), Papanicolaou Test (mesh), 0801 Artificial Intelligence and Image Processing (for), 0903 Biomedical Engineering (for), 0906 Electrical and Electronic Engineering (for), Medical Informatics (science-metrix), 4003 Biomedical engineering (for-2020), 4601 Applied computing (for-2020), 4603 Computer vision and multimedia computation (for-2020)

Popis súboru: application/pdf

Prístupová URL adresa: https://escholarship.org/uc/item/3vv6b76k
https://escholarship.org/content/qt3vv6b76k/qt3vv6b76k.pdf

Evaluation of an automated phenotyping algorithm for rheumatoid arthritis

Autori: Zheng, Henry W Ranganath, Veena K Perry, Lucas C a ďalší

Zdroj: Journal of Biomedical Informatics. 135

Predmety: 46 Information and Computing Sciences (for-2020), 4601 Applied Computing (for-2020), Rheumatoid Arthritis (rcdc), Arthritis (rcdc), Clinical Research (rcdc), Autoimmune Disease (rcdc), 7.3 Management and decision making (hrcs-rac), 7.1 Individual care needs (hrcs-rac), Inflammatory and immune system (hrcs-hc), Humans (mesh), Electronic Health Records (mesh), Algorithms (mesh), Knowledge Bases (mesh), Phenotype (mesh), Arthritis, Rheumatoid (mesh), Phenotyping algorithm, Computational phenotyping, Rheumatoid arthritis, PheKB, Humans (mesh), Arthritis, Rheumatoid (mesh), Phenotype (mesh), Algorithms (mesh), Knowledge Bases (mesh), Electronic Health Records (mesh), Computational phenotyping, PheKB, Phenotyping algorithm, Rheumatoid arthritis, Humans (mesh), Electronic Health Records (mesh), Algorithms (mesh), Knowledge Bases (mesh), Phenotype (mesh), Arthritis, Rheumatoid (mesh), 06 Biological Sciences (for), 08 Information and Computing Sciences (for), 11 Medical and Health Sciences (for), Biomedical Engineering (science-metrix), Medical Informatics (science-metrix), 4203 Health services and systems (for-2020), 4601 Applied computing (for-2020)

Popis súboru: application/pdf

Prístupová URL adresa: https://escholarship.org/uc/item/9pd5z853
https://escholarship.org/content/qt9pd5z853/qt9pd5z853.pdf

Porting of an Atmospheric Chemistry Solver to Parallel CPU-GPU Execution

Autori: Guzman Ruiz, Christian

Thesis Advisors: Acosta, Mario C. (Mario César), César Galobardes, Eduardo

Zdroj: TDX (Tesis Doctorals en Xarxa)

Predmety: Informàtica d'alt rendiment, High-Performance Computing, Computación de alto rendimient, GPU, Models climàtics químics, Chemistry Climate models, Modelos climáticos químicos, Tecnologies

Popis súboru: application/pdf

Prístupová URL adresa: http://hdl.handle.net/10803/693090

Massive cosmological data generation and distribution

Autori: Tallada Crespi, Pau

Thesis Advisors: Tonello , Nadia, Carretero Palacios, Jorge, César Galobardes, Eduardo

Zdroj: TDX (Tesis Doctorals en Xarxa)

Predmety: Gestió de dades, Data management, Gestión de datos, Distribució de dades, Data distribution, Distribución de datos, Optimització d'algorismes, Algorithm optimization, Optimización de algoritmos, Tecnologies

Popis súboru: application/pdf

Prístupová URL adresa: http://hdl.handle.net/10803/691707

Machine learning classification of diagnostic accuracy in pathologists interpreting breast biopsies

Autori: Brunyé, Tad T Booth, Kelsey Hendel, Dalit a ďalší

Zdroj: Journal of the American Medical Informatics Association. 31(3)

Predmety: 46 Information and Computing Sciences (for-2020), 4603 Computer Vision and Multimedia Computation (for-2020), Cancer (rcdc), Patient Safety (rcdc), Women's Health (rcdc), Machine Learning and Artificial Intelligence (rcdc), Networking and Information Technology R&D (NITRD) (rcdc), Breast Cancer (rcdc), Behavioral and Social Science (rcdc), Basic Behavioral and Social Science (rcdc), Clinical Research (rcdc), 4.2 Evaluation of markers and technologies (hrcs-rac), 4.1 Discovery and preclinical testing of markers and technologies (hrcs-rac), Humans (mesh), Pathologists (mesh), Breast (mesh), Algorithms (mesh), Biopsy (mesh), Machine Learning (mesh), breast pathology, medical education, medical residency training, machine learning, diagnostic decision-making, medical image interpretation, diagnostic accuracy, Breast (mesh), Humans (mesh), Biopsy (mesh), Algorithms (mesh), Machine Learning (mesh), Pathologists (mesh), breast pathology, diagnostic accuracy, diagnostic decision-making, machine learning, medical education, medical image interpretation, medical residency training, Humans (mesh), Pathologists (mesh), Breast (mesh), Algorithms (mesh), Biopsy (mesh), Machine Learning (mesh), 08 Information and Computing Sciences (for), 09 Engineering (for), 11 Medical and Health Sciences (for), Medical Informatics (science-metrix), 32 Biomedical and clinical sciences (for-2020), 42 Health sciences (for-2020), 46 Information and computing sciences (for-2020)

Popis súboru: application/pdf

Prístupová URL adresa: https://escholarship.org/uc/item/1d62s5j9
https://escholarship.org/content/qt1d62s5j9/qt1d62s5j9.pdf

Adaptive learning algorithms to optimize mobile applications for behavioral health: guidelines for design decisions.

Autori: Figueroa, Caroline A Aguilera, Adrian Chakraborty, Bibhas a ďalší

Zdroj: Journal of the American Medical Informatics Association. 28(6)

Predmety: Health Services, Clinical Research, Behavioral and Social Science, Basic Behavioral and Social Science, Generic health relevance, Good Health and Well Being, Algorithms, Humans, Machine Learning, Mobile Applications, Reproducibility of Results, Telemedicine, telemedicine, machine learning, algorithms, implementation science, behavioral medicine, Information and Computing Sciences, Engineering, Medical and Health Sciences, Medical Informatics

Prístupová URL adresa: https://escholarship.org/uc/item/2d96h5q3

Lossless Pangenome Indexing Using Tag Arrays

Autori: Eskandar, P Paten, B Sirén, J

Zdroj: Leibniz International Proceedings in Informatics Lipics. 344

Predmety: 46 Information and computing sciences (for-2020)

Popis súboru: application/pdf

Prístupová URL adresa: https://escholarship.org/uc/item/09j4x7gz
https://escholarship.org/content/qt09j4x7gz/qt09j4x7gz.pdf

Post-quantum cryptography acceleration for next generation computers

Autori: Kostalampros, Ioannis-Vatistas

Prispievatelia: University/Department: Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors

Thesis Advisors: Moretó Planas, Miquel, Hernández Luz, Carles

Zdroj: TDX (Tesis Doctorals en Xarxa)

Predmety: Àrees temàtiques de la UPC::Informàtica, 004 - Informàtica

Popis súboru: application/pdf

Prístupová URL adresa: http://hdl.handle.net/10803/695219
https://dx.doi.org/10.5821/dissertation-2117-441612

Development of an automated phenotyping algorithm for hepatorenal syndrome.

Autori: Koola, Jejo D Davis, Sharon E Al-Nimri, Omar a ďalší

Predmety: Humans, Hepatorenal Syndrome, Liver Cirrhosis, Diagnosis, Computer-Assisted, Odds Ratio, Retrospective Studies, ROC Curve, Phenotype, Algorithms, Natural Language Processing, Aged, Middle Aged, Female, Male, Electronic Health Records, Acute Kidney Injury, Support Vector Machine, Acute kidney injury, Cirrhosis, Dimension reduction, Hepatorenal syndrome, Natural language processing, Phenotyping, Clinical Research, Digestive Diseases, Good Health and Well Being, Biological Sciences, Information and Computing Sciences, Medical and Health Sciences, Biomedical Engineering, Medical Informatics

Popis súboru: application/pdf

Prístupová URL adresa: https://escholarship.org/uc/item/9jp8x16p
https://escholarship.org/content/qt9jp8x16p/qt9jp8x16p.pdf

Embedding electronic health records onto a knowledge network recognizes prodromal features of multiple sclerosis and predicts diagnosis

Autori: Nelson, Charlotte A Bove, Riley Butte, Atul J a ďalší

Zdroj: Journal of the American Medical Informatics Association. 29(3)

Predmety: Brain Disorders, Clinical Research, Neurodegenerative, Patient Safety, Neurosciences, Multiple Sclerosis, Networking and Information Technology R&D (NITRD), 8.4 Research design and methodologies (health services), Health and social care services research, Generic health relevance, Neurological, Good Health and Well Being, Algorithms, Electronic Health Records, Humans, Machine Learning, Precision Medicine, knowledge graph, electronic health records, multiple sclerosis, preventative medicine, Information and Computing Sciences, Engineering, Medical and Health Sciences, Medical Informatics

Popis súboru: application/pdf

Prístupová URL adresa: https://escholarship.org/uc/item/47m9r8qv
https://escholarship.org/content/qt47m9r8qv/qt47m9r8qv.pdf