Gliomas Disease Prediction: An Optimized Ensemble Machine Learning-Based Approach

J Thakur, C Choudhary, H Gobind… - 2023 3rd International …, 2023 - ieeexplore.ieee.org
The most frequent primary brain tumors are gliomas, which call for precise prognostic
models for early detection and individualized care. For optimum treatment planning and …

An Optimized Sign Language Recognition Using Convolutional Neural Networks (CNNs) and Tensor-Flow

C Choudhary, N Vyas, UK Lilhore - 2023 3rd International …, 2023 - ieeexplore.ieee.org
Sign language is an essential means of communication for people with hearing disabilities.
However, there is often a communication gap between hearing and non-hearing individuals …

Evaluation of a Fintech Sales Synthetic Data Generation Model Using a Generative Adversarial Network

FA Lopez, M Duran-Riveros… - … Science and Its …, 2024 - Springer
The need for more and better information for decision making is fundamental in modern
organizations, especially in the financial industry. One type of this information is time series …

Chronic Kidney Disease Prediction Using Robust Approach in Machine Learning

N Vyas, V Sharma, D Balla - 2023 3rd International …, 2023 - ieeexplore.ieee.org
The degenerative condition known as Chronic Kidney Disease (CKD) impairs kidney
function and causes waste products to build up in the body. Early CKD prediction and …

Diabetic Retinopathy Detection: A Transfer Learning Based Approach for Accurate Diagnosis

C Choudhary, A Mathur, R Gupta - … International Conference on …, 2023 - ieeexplore.ieee.org
Diabetes patients run the risk of getting diabetic retinopathy, a serious and occasionally
blinding eye condition. One of its distinguishing features is harm done to the bloodstream …

Robustness of Generative Adversarial CLIPs Against Single-Character Adversarial Attacks in Text-to-Image Generation

P Chanakya, P Harsha, KP Singh - IEEE Access, 2024 - ieeexplore.ieee.org
Generative Adversarial Networks (GANs) have emerged as a powerful type of generative
model, particularly effective at creating images from textual descriptions. Similar to diffusion …

Boosting the Accuracy of Cardiovascular Disease Prediction Through SMOTE

R Punugoti, V Dutt, A Kumar… - … Conference on IoT …, 2023 - ieeexplore.ieee.org
Cardiovascular Disease (CVD) affects deaths and hospitalisations. Clinical data analytics
struggles to predict heart disease survival. This report compares machine learning-based …

Automating Data Analysis with Python: A Comparative Study of Popular Libraries and their Application

P Bhardwaj, C Choudhury… - 2023 3rd International …, 2023 - ieeexplore.ieee.org
In areas like businesses, finance, and science, data analysis plays a very important role.
Data analysis needs to be automated to improve productivity and eliminate human error as …

A Machine Learning-Based Algorithm for Early Detection of Sepsis in Hospitalized Patients: Development and Evaluation

VR Burugadda, PM Mane, A Kumar… - 2023 1st International …, 2023 - ieeexplore.ieee.org
Early sepsis detection improves patient outcomes and care. This research provides a
Machine Learning (ML) system for hospitalized sepsis detection. Gradient boosting, an …

Understanding Biomedical Engineering for Quantum Computing

R Agrawal, VG Diaz - Quantum Innovations at the Nexus of …, 2024 - igi-global.com
Engineers working in the biomedical field have a wide range of responsibilities, such as
helping to introduce a new medical imaging technology or to create assiduous devices to …