Machine Learningcloud-Based Approach to Identify and Classify Disease
- Title
- Machine Learningcloud-Based Approach to Identify and Classify Disease
- Creator
- Gupta B.; Alagdeve V.D.; Padmaja P.; Coumaressin T.; Reddy V.N.K.; Kumar R.G.
- Description
- The term "Internet of Things"(IoT) describes the process of creating and modeling web-related physical objects across computing systems. IoT-based healthcare applications have offered multiple real-time products and benefits in recent years. For millions of people, these programmers provide hospitalization can get regular medical records and healthy lives. The introduction of IoT devices in the health sector has several technological developments. This study uses the IoT to construct a disease diagnostic system. Wearable sensors in this system initially monitor the patient's sympathy impulses. The impulses are then sent by a network environment to a server. In addition, a new hybrid approach to evaluation decision-making was presented as part of this research. This technique starts with the development of a set of features of the patient's pulses. Based on a learning approach qualifications are neglected. A fuzzy neural model was used as a diagnostic tool. A specific diagnosis of a particular ailment, such as the diagnosis of a patient's normal and abnormal pulse or the assessment of insulin issues, would be modeled to assess this technology. 2022 IEEE.
- Source
- MysuruCon 2022 - 2022 IEEE 2nd Mysore Sub Section International Conference
- Date
- 2022-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Healthcare; Hybrid Decision Making; Internet of Things; Machine Learning Model
- Coverage
- Gupta B., Siddhant College of Engineering, Department of I.T., Pune, India; Alagdeve V.D., Yeshwantrao Chavan College of Engineering, Department of Electronics Engineering, Nagpur, India; Padmaja P., Teegala Krishna Reddy Engineering College, Department of Electronics and Communication Engineering, Hyderabad, India; Coumaressin T., Sri Manakula Vinayagar Engineering College, Puducherry, India; Reddy V.N.K., Shri Jagdishprasad Jhabarmal Tibrewala University, Department of Computer Science & Engineering, Jhunjhunu, India; Kumar R.G., School of Engineering and Technology Christ (Deemed to Be University), Computer Science and Engineering, Bangalore, India
- Rights
- Restricted Access
- Relation
- ISBN: 978-166549790-9
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Gupta B.; Alagdeve V.D.; Padmaja P.; Coumaressin T.; Reddy V.N.K.; Kumar R.G., “Machine Learningcloud-Based Approach to Identify and Classify Disease,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 24, 2025, https://archives.christuniversity.in/items/show/20179.