Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
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This Author published in this journals
All Journal International Journal of Artificial Intelligence
Mohanchandra, Kusuma
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management

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Brain Computer Interface for Emergency Virtual Voice Arpitha; Binduja; Jahnavi; Mohanchandra, Kusuma
International Journal of Artificial Intelligence Vol 8 No 1 (2021)
Publisher : Lamintang Education and Training Centre, in collaboration with the International Association of Educators, Scientists, Technologists, and Engineers (IA-ESTE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36079/lamintang.ijai-0801.222

Abstract

Brain computer interface (BCI) is one of the thriving emergent technology which acts as an interface between a brain and an external device. BCI for speech communication is acquiring recognition in various fields. Speech is one of the most natural ways to express thoughts and feelings by articulate vocal sounds. The purpose of this study is to restore communication ability of the people suffering from severe muscular disorders like amyotrophic lateral sclerosis (ALS), stroke which causes paralysis, locked-in syndrome, tetraplegia and Myasthenia gravis. They cannot interact with their environment even though their intellectual capabilities are intact. Our work attempts to provide summary of the research articles being published in reputed journals which lead to the investigation of published BCI articles, BCI prototypes, Bio-Signals for BCI, intent of the articles, target applications, classification techniques, algorithms and methodologies, BCI system types. Thus, the result of detailed survey presents an outline of available studies, recent results and looks forward to future developments which provides a communication pathway for paralyzed patients to convey their needs.
Early Detection of Alzheimer’s Disease using Convolutional Neural Network Architecture Kamath, Deepthi; Fathima, Misba Firdose; K. P, Monica; Mohanchandra, Kusuma
International Journal of Artificial Intelligence Vol 8 No 2: December 2021
Publisher : Lamintang Education and Training Centre, in collaboration with the International Association of Educators, Scientists, Technologists, and Engineers (IA-ESTE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36079/lamintang.ijai-0802.232

Abstract

Alzheimer's disease is an extremely popular cause of dementia which leads to memory loss, problem-solving and other thinking abilities that are severe enough to interfere with daily life. Detection of Alzheimer’s at a prior stage is crucial as it can prevent significant damage to the patient’s brain. In this paper, a method to detect Alzheimer’s Disease from Brain MRI images is proposed. The proposed approach extracts shape features and texture of the Hippocampus region from the MRI scans and a Neural Network is used as a Multi-Class Classifier for detection of AD. The proposed approach is implemented and it gives better accuracy as compared to conventional approaches. In this paper, Convolutional Neural Network is the Neural Network approach used for the detection of AD at a prodromal stage.
Blockchain Based Framework for Secure Data Sharing of Medicine Supply Chain in Health Care System Sahana; Thejashwini; Kamath, Vagdevi; Lahari, Yaparla; Mohanchandra, Kusuma
International Journal of Artificial Intelligence Vol 9 No 1: June 2022
Publisher : Lamintang Education and Training Centre, in collaboration with the International Association of Educators, Scientists, Technologists, and Engineers (IA-ESTE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36079/lamintang.ijai-0901.358

Abstract

The potential for blockchain technology in the healthcare sector is summarize in this study. It covers a wide range of technology themes, including storing medical information in blockchains, patient personal data ownership, and patient outreach via mobile apps. Blockchain was created to safeguard digital money transactions, but it has since gained popularity in a variety of other industries, including tourism, real estate, voting, the stock market, and supply chain management. In the healthcare industry, blockchain technology is rapidly gaining traction. Threats to integrity as well as threats to threats to threats to threats to threats to threats to Data management and medicine traceability are two of the most well-known blockchain uses in healthcare. We've explored the problems with standard data processing and drug tracing approaches in this paper.
Co-Authors Arpitha Binduja Fathima, Misba Firdose Jahnavi K. P, Monica Kamath, Deepthi Kamath, Vagdevi Lahari, Yaparla Sahana Thejashwini