BAED: A secured biometric authentication system using ECG signal based on deep learning techniques

AJ Prakash, KK Patro, M Hammad… - Biocybernetics and …, 2022 - Elsevier
Biometric authentication technology has become increasingly common in our daily lives as
information protection and control regulation requirements have grown worldwide. A …

[HTML][HTML] Application of Kronecker convolutions in deep learning technique for automated detection of kidney stones with coronal CT images

KK Patro, JP Allam, BC Neelapu, R Tadeusiewicz… - Information …, 2023 - Elsevier
Kidney stone disease is a serious public health concern that is getting worse with changes
in diet, obesity, medical conditions, certain supplements etc. A kidney stone also called a …

Automated detection of myocardial infarction and heart conduction disorders based on feature selection and a deep learning model

M Hammad, SA Chelloug, R Alkanhel, AJ Prakash… - Sensors, 2022 - mdpi.com
An electrocardiogram (ECG) is an essential piece of medical equipment that helps diagnose
various heart-related conditions in patients. An automated diagnostic tool is required to …

A deep learning technique for biometric authentication using ECG beat template matching

AJ Prakash, KK Patro, S Samantray, P Pławiak… - Information, 2023 - mdpi.com
An electrocardiogram (ECG) is a unique representation of a person's identity, similar to
fingerprints, and its rhythm and shape are completely different from person to person …

A pilot study on AI-driven approaches for classification of mental health disorders

N Dhariwal, N Sengupta, M Madiajagan… - Frontiers in Human …, 2024 - frontiersin.org
The increasing prevalence of mental disorders among youth worldwide is one of society's
most pressing issues. The proposed methodology introduces an artificial intelligence-based …

A new approach of transparent and explainable artificial intelligence technique for patient-specific ecg beat classification

AJ Prakash, KK Patro, S Saunak, P Sasmal… - IEEE Sensors …, 2023 - ieeexplore.ieee.org
Electrocardiogram (ECG) signals carried important clinical information in the form of
intervals and amplitude or morphology. Therefore, it is very important to identify these …

Identification of Lacerations Caused by Cervical Cancer through a comparative study among texture-extraction techniques

J Aguilar-Santiago, JT Guillen-Bonilla… - Applied Sciences, 2023 - mdpi.com
Cervical cancer is a disease affecting a worrisomely large number of women worldwide. If
not treated in a timely fashion, this disease can lead to death. Due to this problematic, this …

ECG signal classification in wearable devices based on compressed domain

J Hua, B Chu, J Zou, J Jia - Plos one, 2023 - journals.plos.org
Wearable devices are often used to diagnose arrhythmia, but the electrocardiogram (ECG)
monitoring process generates a large amount of data, which will affect the detection speed …

A smartphone enabled deep learning approach for myocardial infarction detection using ECG traces for IoT-based healthcare applications

VS Parupudi, AK Panda, RK Tripathy - IEEE Sensors Letters, 2023 - ieeexplore.ieee.org
The development of artificial intelligence (AI)-based frameworks to detect myocardial
infarction (MI) from electrocardiogram (ECG) data is important for Internet of Things (IoT) …

Design of high performance and energy efficient convolution array for convolution neural network-based image inference engine

S Deepika, V Arunachalam - Engineering Applications of Artificial …, 2023 - Elsevier
The energy efficiency of CNN-based inference engines predominately depends upon Giga-
operations-per-second and power consumption. The sparse-based accelerator compresses …