U. Rajendra Acharya
Ngee Ann Polytechnic
730 Papers
1.7K Citations
U. Rajendra Acharya is an academic researcher from Ngee Ann Polytechnic. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 90, co-authored 570 publications. Previous affiliations of U. Rajendra Acharya include Kumamoto University & University of Southern Queensland.
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Papers
CARES 2.0: Completely Automated Robust Edge Snapper for CIMT measurement in 300 ultrasound images—A two stage paradigm
Filippo Molinari,U. Rajendra Acharya,Guang Zeng,Kristen M. Meiburger,Paulo Sergio Rodrigues,Luca Saba,Jasjit S. Suri +6 more
TL;DR: This paper presents a meta-anatomy of the immune system of the central nervous system, which has been studied in detail in the context of cancer research.
In-shoe Plantar Pressure Distribution in Nonneuropathic Type 2 Diabetic Patients in Singapore
TL;DR: This finding supported the notion that either component of neuropathy needs to be present before plantar pressures are elevated, and patients with diabetes mellitus demonstrated greater pressure-time integrals, implying that this variable might be the first clinical sign observable even before peripheral neuropathy could be tested.
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Automated analysis of small intestinal lamina propria to distinguish normal, Celiac Disease, and Non-Celiac Duodenitis biopsy images
Oliver Faust,Simona De Michele,Joel E.W. Koh,V. Jahmunah,Oh Shu Lih,Aditya Kamath,Prabal Datta Barua,Edward J. Ciaccio,Suzanne K. Lewis,Peter H.R. Green,Govind Bhagat,U. Rajendra Acharya +11 more
TL;DR: In this article , the authors investigated whether Artificial Intelligence (AI) models could assist in distinguishing normal, CD, and NCD (and unaffected individuals) based on the characteristics of small intestinal lamina propria (LP).
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Intelligent personalized shopping recommendation using clustering and supervised machine learning algorithms
Nail Chabane,Achraf Bouaoune,Reda Tighilt,Moloud Abdar,Alix Boc,Etienne Lord,Nadia Jouti Tahiri,Bogdan Mazoure,U. Rajendra Acharya,Vladimir Makarenkov +9 more
TL;DR: In this paper , the authors presented a new grocery recommender system using different traditional machine learning (ML) and deep learning (DL) algorithms, and provided recommendations to users in a real-time manner.
Automated Intracranial Hematoma Classification in Traumatic Brain Injury (TBI) Patients Using Meta-Heuristic Optimization Techniques
Vidhya V,U. Raghavendra,Anjan Gudigar,Praneet Kasula,Yashas Chakole,Ajay Hegde,G. R,Chui Ping Ooi,Edward J. Ciaccio,U. Rajendra Acharya +9 more
TL;DR: The developed automated system can enhance the accuracy of hematoma detection, aid clinicians in the fast interpretation of CT images, and streamline triage workflow.