Saranya et al., 2017 - Google Patents
Intelligent medical data storage system using machine learning approachSaranya et al., 2017
- Document ID
- 11085751383637761613
- Author
- Saranya M
- Selvi M
- Ganapathy S
- Muthurajkumar S
- Ramesh L
- Kannan A
- Publication year
- Publication venue
- 2016 Eighth International Conference on Advanced Computing (ICoAC)
External Links
Snippet
In recent days healthcare domains need a efficient storage and retrieval systems to provide a effective medical services to the health seekers. But there is a vocabulary gap in understanding the medical terminologies due to ambiguity. So, the existing systems need a …
- 238000010801 machine learning 0 title description 7
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F17/30634—Querying
- G06F17/30657—Query processing
- G06F17/30675—Query execution
- G06F17/30684—Query execution using natural language analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F17/30705—Clustering or classification
- G06F17/3071—Clustering or classification including class or cluster creation or modification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
- G06F17/27—Automatic analysis, e.g. parsing
- G06F17/2765—Recognition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
- G06F17/30587—Details of specialised database models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
- G06F17/27—Automatic analysis, e.g. parsing
- G06F17/2785—Semantic analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
- G06F17/27—Automatic analysis, e.g. parsing
- G06F17/2705—Parsing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
- G06F19/32—Medical data management, e.g. systems or protocols for archival or communication of medical images, computerised patient records or computerised general medical references
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/02—Knowledge representation
- G06N5/022—Knowledge engineering, knowledge acquisition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F15/00—Digital computers in general; Data processing equipment in general
- G06F15/18—Digital 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA 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
- G06Q10/00—Administration; Management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA 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
- G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Arora et al. | Mining twitter data for depression detection | |
Yuan et al. | Constructing biomedical domain-specific knowledge graph with minimum supervision | |
Irfan et al. | A survey on text mining in social networks | |
Franzoni et al. | A path-based model for emotion abstraction on facebook using sentiment analysis and taxonomy knowledge | |
US11227183B1 (en) | Section segmentation based information retrieval with entity expansion | |
Li et al. | CIDExtractor: A chemical-induced disease relation extraction system for biomedical literature | |
Frisoni et al. | Phenomena explanation from text: Unsupervised learning of interpretable and statistically significant knowledge | |
Saranya et al. | Intelligent medical data storage system using machine learning approach | |
Frisoni et al. | Unsupervised descriptive text mining for knowledge graph learning | |
Yan et al. | Improving semantic similarity retrieval with word embeddings | |
CN111597330A (en) | Intelligent expert recommendation-oriented user image drawing method based on support vector machine | |
Adhikari et al. | Sentiment classifier and analysis for epidemic prediction | |
Nayak et al. | Epidemic outbreak prediction using artificial intelligence | |
Kinariwala et al. | Onto_TML: Auto-labeling of topic models | |
Mulwad et al. | Generating linked data by inferring the semantics of tables | |
Hidayat et al. | BERT-based Topic Modeling Approach for Malaria Research Publication | |
Chang et al. | Incorporating word embedding into cross-lingual topic modeling | |
Zhu et al. | Construction of transformer substation fault knowledge graph based on a depth learning algorithm | |
Prathyusha et al. | Normalization Methods for Multiple Sources of Data | |
Dorodnykh et al. | Extraction of Facts from Web-Tables based on Semantic Interpretation Tabular Data | |
Ghoulam et al. | Using local grammar for entity extraction from clinical reports | |
Yanling et al. | Research on entity recognition and knowledge graph construction based on TCM medical records | |
Grissette | Drug reaction discriminator within encoder-decoder neural network model: COVID-19 pandemic case study | |
Alnashwan et al. | Multiclass sentiment classification of online health forums using both domain-independent and domain-specific features | |
Wilhelm et al. | Extending semantic context analysis using machine learning services to process unstructured data |