A5100619381- Cerebrovascular and Carotid Artery Diseases
- Cardiovascular Health and Disease Prevention
- Neuroscience and Neural Engineering
- Cardiac Imaging and Diagnostics
- Brain Tumor Detection and Classification
- Acute Ischemic Stroke Management
- AI in cancer detection
- Medical Image Segmentation Techniques
- EEG and Brain-Computer Interfaces
- Muscle activation and electromyography studies
- Hand Gesture Recognition Systems
- Analytical Chemistry and Sensors
- Advanced Neural Network Applications
- Advanced Sensor and Energy Harvesting Materials
- Advanced Memory and Neural Computing
- COVID-19 diagnosis using AI
- Conducting polymers and applications
- Radiomics and Machine Learning in Medical Imaging
- 3D Printing in Biomedical Research
- Gaze Tracking and Assistive Technology
- Phonocardiography and Auscultation Techniques
- Hematological disorders and diagnostics
- Artificial Intelligence in Healthcare
- ECG Monitoring and Analysis
- Rice Cultivation and Yield Improvement
Banaras Hindu University
2019-2024
Indian Institute of Technology BHU
2020-2024
Jagran Lakecity University
2024
Shri Mata Vaishno Devi University
2022-2023
CMR University
2021
Azienda Ospedaliero-Universitaria Cagliari
2021
Rajiv Gandhi Technical University
2021
Barkatullah University
2021
Kathmandu University
2020
Dhulikhel Hospital
2020
Background and Motivation: The novel coronavirus causing COVID-19 is exceptionally contagious, highly mutative, decimating human health life, as well the global economy, by consistent evolution of new pernicious variants outbreaks. reverse transcriptase polymerase chain reaction currently used for diagnosis has major limitations. Furthermore, multiclass lung classification X-ray systems having viral, bacterial, tubercular classes—including COVID-19—are not reliable. Thus, there a need...
Stroke and cardiovascular diseases (CVD) significantly affect the world population. The early detection of such events may prevent burden death costly surgery. Conventional methods are neither automated nor clinically accurate. Artificial Intelligence-based automatically detecting predicting severity CVD stroke in their stages prime importance. This study proposes an attention-channel-based UNet deep learning (DL) model that identifies carotid plaques internal artery (ICA) common (CCA)...
The early detection of carotid wall plaque is recommended in the prevention cardiovascular disease (CVD) moderate-risk patients. Previous techniques for B-mode atherosclerotic segmentation used artificial intelligence (AI) methods on monoethnic databases, where training and testing are from "same" ethnic group ("Seen AI"). Therefore, versatility system questionable. This first study its kind that uses "Unseen AI" paradigm "different" groups. We hypothesized deep learning (DL) models should...
The death due to stroke is caused by embolism of the arteries which rupture atherosclerotic lesions in carotid arteries. lesion formation over time, and thus, early screening recommended for asymptomatic moderate-risk patients. previous techniques adopted conventional methods or semi-automated and, more recently, machine learning solutions. A handful studies have emerged based on solo deep (SDL) models such as UNet architecture.The proposed research first adopt hybrid (HDL) artificial...
Atherosclerotic plaque in carotid arteries can ultimately lead to cerebrovascular events if not monitored. The objectives of this study are (a) design a set artificial intelligence (AI)-based tissue characterization and classification (TCC) systems (Atheromatic 2.0, AtheroPoint, CA, USA) using ultrasound-based artery scans collected from multiple centers (b) evaluate the AI performance. We hypothesize that symptomatic is more scattered than asymptomatic plaque. Therefore, system learn,...
The incidence of cardiovascular diseases (CVD) is rising rapidly worldwide. Some forms CVD, such as stroke and heart attack, are more common among patients with certain conditions. Atherosclerosis development a major factor underlying events, attack stroke, its early detection may prevent events. Ultrasound imaging carotid arteries useful method for diagnosis atherosclerotic plaques; however, an automated to classify plaques evaluation early-stage CVD needed. Here, we propose classification...
Every year, around 17.9 million people die due to Cardiovascular Diseases which is 31% of global deaths. These numbers indicate the need for a system that should be sensitive detect Heart Disease at an early stage. sound signals can give information about heart damage much earlier For proper extraction from auscultation condition, it required are free noise so improper classification as normal abnormal situation eliminated. A number denoising methods have been proposed sounds, both in time...
Chemical fertilizers boost crop production; however, their continued use decreases soil fertility in the long run. Nutrient recycling by beneficiation of poultry manure into biochar and application as a amendment is long-term solution for plant nutrition. The effect manure, irrigation with 50% 100% greywater (GW) was assessed on properties growth wheat (
Ischemic stroke is a major cause of death and disability worldwide. Nowadays, electrical impedance spectroscopy an emerging tool to differentiate between normal conditions.In this study, changes in the bio-impedance using two-electrode method with varying frequencies from 100 35 kHz have been assessed model global cerebral ischemia anesthetized rats during normal, occlusion reperfusion conditions. Global was induced by bilateral common carotid artery for 40 min following reperfusion. The...
In this manuscript, we proposed an automatic segmentation method which was developed using the depth-wise separable convolution with bottleneck connections. The data were normalized group normalization for reducing computational complexities and clipped RELU used ceiling capped at 6. network trained on datasets of brain tumor skin cancer while it tested same as well different acquired under environments. Additionally, case tumor, real-time MRI dataset. quantitative qualitative analysis...
This work addresses the issues of noise and tissue appearance fluctuations in histopathology image classification by using a novel deep ensemble method. The experiment’s images were inherently noisy; however, proposed approach includes features that allow for to be effectively encountered while tasks are being completed. integration streamlines categorization process eliminating requirement separate denoising phase. encompasses studies on two types noise, namely Gaussian Rician, both...
This study presents a biosensor utilizing electrospun SnO
Abstract In this study, we have developed a wireless, portable, standalone, and simple electric cell-substrate impedance sensing (ECIS) system to analyze in-depth functional aspects of cellular functions on the surface co-planar metal electrode coated conventional glass substrate using low-cost circuitry correlated it with an equivalent electrical circuit (EEC) model. Low-cost was used for studying dynamic behavior mouse myoblast cells (C2C12) in culture chamber. Further, ECIS connected...
Heart Stroke is one of the severe health hazards; therefore, early heart stroke prediction helps society to save human lives. This objective can be achieved using machine learning techniques. In this research article, models are applied on well known classification data-set. addition, effect pre-processing data has also been summarized. experimental analysis, and ANN with standard feature selection technique tested data-set, framingham obtained results evaluated confusion metrics includes...
Adherent mammalian cells are susceptible to the physiological conditions, i.e., physicochemical and topological properties of extracellular microenvironment surrounding them. In this paper, cell-substrate interaction is taken as primary step for exhibiting their optimal functions, including cell adhesion, proliferation, migration, differentiation. Herein, change in characteristic transparent semiconducting metal oxide, ZnO thin film a function progression cellular processes functions...
Gait analysis on healthy subjects was performed based surface electromyographic and acceleration sensor signal, implemented through machine learning approaches. The EMG 3-axes signals have been acquired for 5 different terrains: level ground, ramp ascent, descent, stair descent. These were from the tibialis anterior gastrocnemius medial head muscles that correspond to dorsiflexion plantar flexion, respectively. After feature extraction, these are fed conventional classifiers: linear...
Background Fetal weight estimation plays a significant role in the antenatal management of high risk pregnancies. It is also an important parameter for predicting neonatal outcome and informs decision mode intra-partum pregnant women. Among various methods prenatal fetal estimation, most commonly used are clinical sonography.
 Objective The objective this study was to compare accuracy using Johnson’s formula sonographic with actual birth weight.
 Method This prospective conducted...