A5107962880- Dialysis and Renal Disease Management
- Hearing Impairment and Communication
- Hand Gesture Recognition Systems
- Central Venous Catheters and Hemodialysis
- Concrete Corrosion and Durability
- Digital Media Forensic Detection
- Clinical Reasoning and Diagnostic Skills
- Asphalt Pavement Performance Evaluation
- Machine Learning and Data Classification
- Smart Agriculture and AI
- Gait Recognition and Analysis
- Ultrasound in Clinical Applications
- Generative Adversarial Networks and Image Synthesis
- IoT-based Smart Home Systems
- Simulation-Based Education in Healthcare
- Ultrasound and Hyperthermia Applications
- Vascular Procedures and Complications
- Innovations in Medical Education
- Neural Networks and Applications
- Vehicle emissions and performance
- Renal and Vascular Pathologies
- Energy, Environment, and Transportation Policies
- Infrastructure Maintenance and Monitoring
- Radiomics and Machine Learning in Medical Imaging
- Software System Performance and Reliability
Indian Institute of Technology Tirupati
2024
University of Alberta
2023-2024
McMaster University
2021
Deep learning (DL) models for medical image classification frequently struggle to generalize data from outside institutions. Additional clinical are also rarely collected comprehensively assess and understand model performance amongst subgroups. Following the development of a single-center identify lung sliding artifact on ultrasound (LUS), we pursued validation strategy using external LUS data. As annotated relatively scarce—compared other imaging data—we adopted novel technique optimize...
The people in the world who are hearing impaired face many obstacles communication and require an interpreter to comprehend what a person is saying. There has been constant scientific research existing models lack ability make accurate predictions. So we propose deep learning model trained on ASL i.e American Sign Language which will take action form of as input translate it into text. To achieve former Convolution Neural Network based VGG16 architecture used well Tensorflow for image...
Dealing with ageing software is a reality of the industry, and even open source systems. This great opportunity for engineering researchers to apply traditional techniques program analysis solve problems refactoring modernization. The generative AI advancements have opened up whole new world possibilities tasks such as code generation, translation, bug fixing among others. Industry keen on exploring scalable solutions refactoring, automated testing now automatic generation.
Vascular and peritoneal access are essential elements for sustainability of chronic dialysis programs. Data on availability, patterns use, funding models, workforce vascular accesses at a global scale is limited.
Deep learning have a variety of applications in different fields such as computer vision, automated self-driving cars, natural language processing tasks and many more. One deep adversarial architecture changed the fundamentals data manipulation. The inception Generative Adversarial Network (GAN) vision domain drastically way how we saw manipulated data. But this manipulation using GAN has found its application various type malicious activities like creating fake images, swapped videos,...
The proposed system aims to facilitate farmers through a flutter application. goal is have two different interfaces in one single application which will positive impact on the agriculture sector and provide technological assistance farmers. One interface would be deep learning model predict name of disease crop suffering from photo leaf other involves having multilingual answer queries his/her language thus giving him access necessary information pertaining agriculture.
Missing values in a dataset has always been problem for data analysis and modelling. Building model over where the missing are not handled properly will definitely degrade accuracy performance of model. This particularly impacts deterministic models. Knowing that majority models used today makes dealing with crucial before applying machine learning In this paper we have discussed various approaches such as statistical method (using mean), MICE KNN imputing tested their combination two...
The most recent concern of all people on Earth is the increase in concentration greenhouse gas atmosphere. these gases has risen rapidly over last century and if trend continues it can cause many adverse climatic changes. There have been ways implemented to curb this by government limiting processes that emit a higher amount CO2, one such gas. However, there mounting evidence CO2 numbers supplied do not accurately reflect performance automobiles road. Our proposal using artificial...
The people in the world who are hearing impaired face many obstacles communication and require an interpreter to comprehend what a person is saying. There has been constant scientific research existing models lack ability make accurate predictions. So we propose deep learning model trained on ASL i.e. American Sign Language which will take actions form of as input translate it into text. To achieve translation Convolution Neural Network transfer based VGG16 architecture used. improvement...
Potholes and other pavement distresses are a matter of concern. not only cause harm to the vehicles but also endanger lives people driving vehicles. These potholes accidents that take minor back injuries can become serious over period time. In India, as reported by Ministry Road Transport Highways (MoRTH) around 5000 passengers killed every year in road caused potholes. Pothole identification has been dependent upon manual detection, which is neither cost-effective nor time efficient. this...
Abstract Background The COVID-19 pandemic has restricted in-person clinical training for medical students. Simulation-based teaching is a promising tool to introduce learners the environment. MacSim student-led simulation workshop develop competencies. objective of this study was assess impacts and participants’ perspectives regarding simulation-based teaching. Methods A comprehensive simulation, representative virtual care scenario, delivered 42 pre-clerkship students via video...