Bajaj et al., 2023 - Google Patents
Prediction of Mental Health Treatment Adherence using Machine Learning AlgorithmsBajaj et al., 2023
- Document ID
- 7634315736900580931
- Author
- Bajaj M
- Rawat P
- Vats S
- Sharma V
- Gopal L
- et al.
- Publication year
- Publication venue
- 2023 International Conference on Computational Intelligence, Communication Technology and Networking (CICTN)
External Links
Snippet
Mental health is an important part of a person's total well-being. Identifying individuals who require medical intervention for mental health disorders, on the other hand, can be difficult, leading to delayed or insufficient treatment. The goal of this research is to create a prediction …
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
- 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
- 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
- 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
- G06Q50/10—Services
- G06Q50/22—Health care, e.g. hospitals; Social work
-
- 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
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
-
- 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
- G06Q50/01—Social networking
-
- 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
- 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
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Bajaj et al. | Prediction of Mental Health Treatment Adherence using Machine Learning Algorithms | |
Kim et al. | A data-driven artificial intelligence model for remote triage in the prehospital environment | |
Gil et al. | Predicting seminal quality with artificial intelligence methods | |
Yoo et al. | Mining-based lifecare recommendation using peer-to-peer dataset and adaptive decision feedback | |
Tervonen et al. | Personalized mental stress detection with self-organizing map: From laboratory to the field | |
Mentis et al. | Applications of artificial intelligence− machine learning for detection of stress: a critical overview | |
Folorunso et al. | Heart disease classification using machine learning models | |
US20230187041A1 (en) | Real-time method of bio big data automatic collection for personalized lifespan prediction | |
Nguyen et al. | Decision support system for the differentiation of schizophrenia and mood disorders using multiple deep learning models on wearable devices data | |
WO2021240275A1 (en) | Real-time method of bio big data automatic collection for personalized lifespan prediction | |
Ramesh et al. | A Novel Early Detection and Prevention of Coronary Heart Disease Framework Using Hybrid Deep Learning Model and Neural Fuzzy Inference System | |
Kim et al. | Modeling long-term human activeness using recurrent neural networks for biometric data | |
Oliullah et al. | Analyzing the effectiveness of several machine learning methods for heart attack prediction | |
Moosavi et al. | Early mental stress detection using q-learning embedded starling murmuration optimiser-based deep learning model | |
Sani et al. | Review on hypertension diagnosis using expert system and wearable devices | |
Leitner et al. | Classification of patient recovery from COVID-19 symptoms using consumer wearables and machine learning | |
JP2024513618A (en) | Methods and systems for personalized prediction of infections and sepsis | |
Zohra | Prediction of different diseases and development of a clinical decision support system using Naive Bayes classifier | |
Rathi et al. | Comparative Study of Heart Disease Prediction Algorithm | |
Sathiyaraj et al. | Convergence of Big Data and Cognitive Computing in Healthcare | |
Lakshmi et al. | A Review And Analysis Of The Role Of Machine Learning Techniques To Predict Health Risks Among Women During Menopause | |
Wanyana et al. | A Personal Health Agent for Decision Support in Arrhythmia Diagnosis | |
Aishwarya et al. | AutoML Based IoT Application for Heart Attack Risk Prediction | |
Yadav et al. | Behaviour Analysis Using Machine Learning Algorithms In Health Care Sector | |
Stamate et al. | Can artificial neural networks predict psychiatric conditions associated with cannabis use? |