Ganesh et al., 2021 - Google Patents
Diabetes Prediction using Logistic Regression and Feature NormalizationGanesh et al., 2021
- Document ID
- 17665937588339569307
- Author
- Ganesh V
- Kolluri J
- Kumar K
- Publication year
- Publication venue
- 2021 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES)
External Links
Snippet
Diabetes is one of the many major issues in medical field and lakhs of people are affected due to this diabetes. From many years many researches are going on this problem to detect this diabetes. Here we are mainly concerned towards women because during pregnancy …
- 206010012601 Diabetes mellitus 0 title abstract description 63
Classifications
-
- 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
- G06F19/34—Computer-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
- G06F19/345—Medical expert systems, neural networks or other automated diagnosis
-
- 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
- G06F19/34—Computer-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
- G06F19/3431—Calculating a health index for the patient, e.g. for risk assessment
-
- 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
- G06F19/322—Management of patient personal data, e.g. patient records, conversion of records or privacy aspects
-
- 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
- G06F19/34—Computer-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
- G06F19/3437—Medical simulation or modelling, e.g. simulating the evolution of medical disorders
-
- 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
- G06F17/30289—Database design, administration or maintenance
- G06F17/30303—Improving data quality; Data cleansing
-
- 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
- G06K9/6267—Classification techniques
- G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
-
- 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
- G06K9/6267—Classification techniques
- G06K9/6279—Classification techniques relating to the number of classes
-
- 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
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/24—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for machine learning, data mining or biostatistics, e.g. pattern finding, knowledge discovery, rule extraction, correlation, clustering or classification
-
- 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
- G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
- G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/04—Inference methods or devices
-
- 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
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N7/00—Computer systems based on specific mathematical models
- G06N7/005—Probabilistic networks
-
- 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
- G06K9/00127—Acquiring and recognising microscopic objects, e.g. biological cells and cellular parts
- G06K9/00147—Matching; Classification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Islam et al. | Chronic kidney disease prediction based on machine learning algorithms | |
Christo et al. | Feature selection and instance selection from clinical datasets using co-operative co-evolution and classification using random forest | |
CN109659033B (en) | Chronic disease state of an illness change event prediction device based on recurrent neural network | |
Al Jarullah | Decision tree discovery for the diagnosis of type II diabetes | |
WO2021120936A1 (en) | Chronic disease prediction system based on multi-task learning model | |
Katarya et al. | Comparison of different machine learning models for diabetes detection | |
CN113782183B (en) | Device and method for predicting risk of pressure injury based on multi-algorithm fusion | |
Srivastav et al. | Predictive Machine Learning Approaches for Cervical Cancer Detection: An Analytical Comparison | |
Das et al. | A comparative study of machine learning approaches for heart stroke prediction | |
Adigun et al. | Classification of Diabetes Types using Machine Learning | |
Asaad | Support vector machine classification learning algorithm for diabetes prediction | |
CN111986814A (en) | Modeling method of lupus nephritis prediction model of lupus erythematosus patient | |
Ganesh et al. | Diabetes Prediction using Logistic Regression and Feature Normalization | |
Kriještorac et al. | The impact of predictor variables for detection of diabetes mellitus type-2 for Pima Indians | |
Cinar et al. | Development of early stage diabetes prediction model based on stacking approach | |
Murthy | An efficient diabetes prediction system for better diagnosis | |
Anil et al. | Data mining techniques in diabetes prediction and diagnosis: A review | |
Krishna et al. | An Efficient Machine Learning Classification Model for Diabetes Prediction | |
James et al. | Machine learning-based early diabetes prediction | |
Mohapatra et al. | Automated invasive cervical cancer disease detection at early stage through deep learning | |
Faris et al. | Detection of PCOS Based on Genetic Algorithm Coupled with SVM | |
Kadhim et al. | Machine Learning Prediction of Brain Stroke at an Early Stage | |
Gangula et al. | Prediction and Prognosis of Diabetes Using Logistic Regression | |
Rajivkannan et al. | A survey on diabetes prediction using machine learning techniques | |
Faris et al. | Proposed model for detection of PCOS using machine learning methods and feature selection |