V. Mahalakshmi
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
V. Mahalakshmi has a total of 25 co-authors. Here are the top co-authors by number of shared publications:
- Awatef Salem Balobaid
Jazan University
3 shared publications - Konduru Reddy Madhavi
Mohan Babu University (Erstwhile Sree Vidyanikethan Engineering College)
2 shared publications - Manoharan Ramkumar Raja
Electrical Engineering Department, College of Engineering, King Khalid University, Abha 61411, Saudi Arabia
2 shared publications Aluri Gopi
CMR Engineering College
1 shared publication- Bright Kanisha
Indra Ganesan College of Engineering
1 shared publication C. Sateesh Kumar Reddy
Guru Nanak Institute of Technology
1 shared publication
Latest Publications
- 21 June 2025
- Published by Springer Nature
- p. 278-286
An African Vulture Optimization for the Detection of Diabetic Retinopathy
- 21 June 2025
- Published by Springer Nature
- p. 278-286
An African Vulture Optimization for the Detection of Diabetic Retinopathy
- 27 May 2025
- Published by Springer Nature
- p. 490-498
A Fog-Based Security Framework for Smart Agriculture
- 27 May 2025
- Published by Springer Nature
- p. 490-498
A Fog-Based Security Framework for Smart Agriculture
- 29 March 2025
- Published by Springer Nature
- p. 229-243
Conversion of Prompt to Image Generation Using AI Generator
- 29 March 2025
- Published by Springer Nature
- p. 229-243
Conversion of Prompt to Image Generation Using AI Generator
- 27 December 2024
- Published by Springer Nature
- p. 117-131
Brain Tumor Classification from MRI Scans Using a Novel CNN Architecture and Optimization Techniques
- 27 December 2024
- Published by Springer Nature
- p. 117-131
Brain Tumor Classification from MRI Scans Using a Novel CNN Architecture and Optimization Techniques
- 28 March 2023
- Published by Springer Nature
- p. 543-551
Federated Learning and Adaptive Privacy Preserving in Healthcare
- 28 March 2023
- Published by Springer Nature
- p. 543-551
Federated Learning and Adaptive Privacy Preserving in Healthcare
- Open Access
- 14 March 2023
- Published by MDPI AG in Healthcare
- Vol. 11 (6) , 854
Artificial Intelligence: A Next-Level Approach in Confronting the COVID-19 Pandemic
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which caused coronavirus diseases (COVID-19) in late 2019 in China created a devastating economical loss and loss of human lives. To date, 11 variants have been identified with minimum to maximum severity of infection and surges in cases. Bacterial co-infection/secondary infection is identified during viral respiratory infection, which is a vital reason for morbidity and mortality. The occurrence of secondary infections is an additional burden to the healthcare system; therefore, the quick diagnosis of both COVID-19 and secondary infections will reduce work pressure on healthcare workers. Therefore, well-established support from Artificial Intelligence (AI) could reduce the stress in healthcare and even help in creating novel products to defend against the coronavirus. AI is one of the rapidly growing fields with numerous applications for the healthcare sector. The present review aims to access the recent literature on the role of AI and how its subfamily machine learning (ML) and deep learning (DL) are used to curb the pandemic’s effects. We discuss the role of AI in COVID-19 infections, the detection of secondary infections, technology-assisted protection from COVID-19, global laws and regulations on AI, and the impact of the pandemic on public life.
- 14 March 2023
- Published by MDPI AG in Healthcare
- Vol. 11 (6) , 854
Open AccessArtificial Intelligence: A Next-Level Approach in Confronting the COVID-19 Pandemic
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which caused coronavirus diseases (COVID-19) in late 2019 in China created a devastating economical loss and loss of human lives. To date, 11 variants have been identified with minimum to maximum severity of infection and surges in cases. Bacterial co-infection/secondary infection is identified during viral respiratory infection, which is a vital reason for morbidity and mortality. The occurrence of secondary infections is an additional burden to the healthcare system; therefore, the quick diagnosis of both COVID-19 and secondary infections will reduce work pressure on healthcare workers. Therefore, well-established support from Artificial Intelligence (AI) could reduce the stress in healthcare and even help in creating novel products to defend against the coronavirus. AI is one of the rapidly growing fields with numerous applications for the healthcare sector. The present review aims to access the recent literature on the role of AI and how its subfamily machine learning (ML) and deep learning (DL) are used to curb the pandemic’s effects. We discuss the role of AI in COVID-19 infections, the detection of secondary infections, technology-assisted protection from COVID-19, global laws and regulations on AI, and the impact of the pandemic on public life.