IEEE

An Evaluation of Medical Image Analysis using Image Segmentation and Deep Learning Techniques for Brain-Tumour

Abstract: An aberrant mass of rapidly proliferating brain cells, known as a brain tumour, may develop into various forms of cancer. The segmentation of brain tumours by MRI scans is a challenging but ...
IEEE

ECHO-SegNet Framework for Accurate 2D Echocardiographic Image Segmentation Using the CAMUS Dataset

Abstract: Accurate segmentation of cardiac structures in echocardiographic images plays a vital role in the quantitative assessment of cardiac function, enabling early detection and management of ...
IEEE

Empowering Educators with AI: A System for Designing Integrated STEM Projects Using Machine Learning and Large Language Models

Abstract: Integrated STEM projects and experiments promote interdisciplinary learning, enhance critical thinking, and prepare students for real-world problem-solving by bridging science, technology, ...
IEEE

Early Detection of Alzheimer's Disease Using Machine Learning Techniques

Abstract: Alzheimer's disease (AD) is a disease of the central nervous system that manifests as dementia and other mental disorders. It's critical to correctly diagnose Alzheimer's disease as well as ...
SciELO

Artificial intelligence in the diagnosis and management of dysphagia: a scoping review

Purpose This scoping review aimed to map and synthesize evidence on technological advancements using Artificial Intelligence in the diagnosis and management of dysphagia. We followed the PRISMA ...
IEEE

Mask R-CNN with HRNet Backbone for Person Detection Evaluation on COCO Using mIoU and Threshold Optimization

Abstract: A crucial computer vision problem is person detection, but real-world challenges including crowded backgrounds, inconsistent lighting, and object occlusion require accurate and robust models ...
IEEE

A Novel Deep Learning-Based Approach for Brain Tumor Segmentation and Classification Using Diffusion-Weighted Imaging and Magnetic Resonance Spectroscopy

Abstract: Brain tumours (BT) are a dangerous condition that gets a lot of attention. They can be fatal. However, for effective treatment and life-saving measures, early detection and tumour type and ...
IEEE

On Road Vehicle Breakdown Assistance by Using Machine Learning

Abstract: The On Road Vehicle Breakdown Application (ORVBA) functions as an optimal system to resolve remote automotive breakdowns. Primary end-users of the ORVBA platform will use the system to reach ...
IEEE

Physically-Aware Qubit Reuse for Optimized Quantum Circuit Compilation Using Machine Learning

Recently developed quantum computers support mid-circuit measurements, allowing qubit measurement, resetting, and reuse during the execution of quantum circuits. This capability opens new ...
BMJ

Predicting cardiovascular events from routine mammograms using machine learning

10 The George Institute for Global Health, School of Public Health, Imperial College London, London, UK Background Cardiovascular risk is underassessed in women. Many women undergo screening ...
IEEE

Chronic Kidney Disease Risk Prediction Using Machine Learning

Abstract: Chronic kidney disease is one of the fast-growing global health issues that necessitates early detection for effective management and treatment. This research article examines the ...
IEEE

An Analysis of City Image by Exploiting Social Media: Toward a Deeper Understanding of Multiple Characteristics and Their Temporal Changes Using Machine Learning

Abstract: Since successful city branding plays a crucial role in establishing a city’s competitiveness and uniqueness, cities worldwide are actively involved in shaping their city images. City images ...