[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Zaghir et al., 2021 - Google Patents

Real-world patient trajectory prediction from clinical notes using artificial neural networks and UMLS-based extraction of concepts

Zaghir et al., 2021

View PDF
Document ID
2554534010478426971
Author
Zaghir J
Rodrigues-Jr J
Goeuriot L
Amer-Yahia S
Publication year
Publication venue
Journal of Healthcare Informatics Research

External Links

Snippet

As more data is generated from medical attendances and as Artificial Neural Networks gain momentum in research and industry, computer-aided medical prognosis has become a promising technology. A common approach to perform automated prognoses relies on …
Continue reading at pmc.ncbi.nlm.nih.gov (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
    • G06F19/345Medical expert systems, neural networks or other automated diagnosis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/32Medical data management, e.g. systems or protocols for archival or communication of medical images, computerised patient records or computerised general medical references
    • G06F19/322Management of patient personal data, e.g. patient records, conversion of records or privacy aspects
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • G06N5/02Knowledge representation
    • G06N5/022Knowledge engineering, knowledge acquisition
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30289Database design, administration or maintenance
    • G06F17/30303Improving data quality; Data cleansing
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/20Handling natural language data
    • G06F17/27Automatic analysis, e.g. parsing
    • G06F17/2765Recognition
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
    • G06Q50/10Services
    • G06Q50/22Health care, e.g. hospitals; Social work
    • G06Q50/24Patient record management
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • G06N5/04Inference methods or devices
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/3061Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/10Office automation, e.g. computer aided management of electronic mail or groupware; Time management, e.g. calendars, reminders, meetings or time accounting
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00Computer systems based on specific mathematical models
    • G06N7/005Probabilistic networks
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F15/00Digital computers in general; Data processing equipment in general
    • G06F15/18Digital computers in general; Data processing equipment in general in which a programme is changed according to experience gained by the computer itself during a complete run; Learning machines
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation

Similar Documents

Publication Publication Date Title
Sha et al. Interpretable predictions of clinical outcomes with an attention-based recurrent neural network
Denecke et al. Sentiment analysis of clinical narratives: a scoping review
Luo et al. Review of natural language processing in radiology
US20200356846A1 (en) Prediction of healthcare outcomes and recommendation of interventions using deep learning
Nigam Applying deep learning to ICD-9 multi-label classification from medical records
Yu et al. Enhancing healthcare through large language models: A study on medical question answering
US11176441B2 (en) Neural network architecture for performing medical coding
Zhu et al. Using deep learning based natural language processing techniques for clinical decision-making with EHRs
Guo et al. Disease inference with symptom extraction and bidirectional recurrent neural network
Agarwal et al. Preparing for the next pandemic via transfer learning from existing diseases with hierarchical multi-modal BERT: a study on COVID-19 outcome prediction
Henriksson et al. Modeling heterogeneous clinical sequence data in semantic space for adverse drug event detection
Zaghir et al. Real-world patient trajectory prediction from clinical notes using artificial neural networks and UMLS-based extraction of concepts
Manda et al. Taking a dive: Experiments in deep learning for automatic ontology-based annotation of scientific literature
Al-Bashabsheh et al. Improving clinical documentation: automatic inference of ICD-10 codes from patient notes using BERT model
Hasan et al. Predicting the outcome of patient-provider communication sequences using recurrent neural networks and probabilistic models
Moreno-Barea et al. Clinical text classification in cancer real-world data in spanish
Naseem et al. Graph learning with label attention and hyperbolic embedding for temporal event prediction in healthcare
Rajathi et al. Named entity recognition-based hospital recommendation
Schiegl Disease-Symptom relation extraction from medical text corpora with BERT
Luo et al. Automated Extraction of Patient-Centered Outcomes After Breast Cancer Treatment: An Open-Source Large Language Model–Based Toolkit
Zafari et al. Using deep learning with canadian primary care data for disease diagnosis
Shibly et al. Transfer learning in classifying prescriptions and keyword-based medical notes
Merchant et al. Ensemble neural models for ICD code prediction using unstructured and structured healthcare data
Long et al. Ensemble DeBERTa Models on USMLE Patient Notes Automatic Scoring using Note-based and Character-based approaches
Lin et al. Adapting static and contextual representations for policy gradient-based summarization