APPLICATION OF MACHINE LEARNING IN BEHAVIORAL MODIFICATION
| Title: | APPLICATION OF MACHINE LEARNING IN BEHAVIORAL MODIFICATION |
|---|---|
| Authors: | Sudeep Varshney, Aditi Chandra, Pushpendra Kumar Rajput, Sunil Kumar, Gunjan Varshney |
| Source: | Proceedings on Engineering Sciences, Vol 6, Iss 4, Pp 1585-1592 (2024) |
| Publisher Information: | University of Kragujevac, 2024. |
| Publication Year: | 2024 |
| Collection: | LCC:Engineering (General). Civil engineering (General) |
| Subject Terms: | behavioral modification, big data, brain computer interface, healthcare, iot, machine learning, Engineering (General). Civil engineering (General), TA1-2040 |
| More Details: | Machine Learning centers on applications that gain for a fact and further develop their dynamic or prescient exactness over the long run. Behavioral Modification is the use of basic learning techniques such as conditioning, biofeedback, assertiveness training, positive or negative reinforcement, aversion therapy to change unwanted individual or group behavior. Behavior change is vital to addressing both the challenges facing human health and wellbeing and to promoting the uptake of research findings in health policy and practice. This paper provides a solution about the utilization of machine learning in behavioral modification by giving some real-time examples. The device based on machine learning is used to develop and evaluate a ‘Knowledge System’ that automatically extracts, synthesizes, and interprets findings from Brain Computer Interface (BCI) evaluation reports to generate new insights to conduct change and further develop forecast of intervention viability and permits clients to effectively and productively examine the framework to find solutions. Organizations engaged in healthcare are charged with the complex task of keeping expenses down without compromising healthcare quality. The key prerequisite is to focus instead of fix, with the greatest test being the need to follow up on enormous volumes of totaled medical care driven Big Data. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 2620-2832 2683-4111 |
| Relation: | https://pesjournal.net/journal/v6-n4/17.pdf; https://doaj.org/toc/2620-2832; https://doaj.org/toc/2683-4111 |
| DOI: | 10.24874/PES06.04.017 |
| Access URL: | https://doaj.org/article/3078b33cb11b4e699958914aa7024216 |
| Accession Number: | edsdoj.3078b33cb11b4e699958914aa7024216 |
| Database: | Directory of Open Access Journals |
| ISSN: | 26202832 26834111 |
|---|---|
| DOI: | 10.24874/PES06.04.017 |
| Published in: | Proceedings on Engineering Sciences |
| Language: | English |