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Predicting patients with Parkinson's disease using Machine Learning and ensemble voting technique
Parkinson's disease is the second most common neurological disorder that causes
significant physical disabilities, decreases the quality of life, and does not have a cure …
significant physical disabilities, decreases the quality of life, and does not have a cure …
The future of telemedicine: Emerging technologies, challenges, and opportunities
R Damaševičius, OO Abayomi-Alli - Metaverse Applications for …, 2024 - igi-global.com
Telemedicine, or the delivery of healthcare services via distant communication technology,
has grown in importance in recent years. Telemedicine has the ability to alter healthcare …
has grown in importance in recent years. Telemedicine has the ability to alter healthcare …
A novel hybrid CNN-KNN ensemble voting classifier for Parkinson's disease prediction from hand sketching images
Parkinson's disease is a progressive neurodegenerative disorder that causes significant
physical disabilities and reduces the quality of life. This disease is caused by the loss of …
physical disabilities and reduces the quality of life. This disease is caused by the loss of …
A Sco** Review of Large Language Models: Architecture and Applications
H Moujahid, K Boutahar, O El Gannour… - … Research in Applied …, 2024 - ieeexplore.ieee.org
Large Language Models (LLMs) have recently exhibited impressive usability of natural
language processing to perform different outcomes. A plethora of research contributions …
language processing to perform different outcomes. A plethora of research contributions …
Improving skin diseases prediction through data balancing via classes weighting and transfer learning
Skin disease prediction using artificial intelligence has shown great potential in improving
early diagnosis and treatment outcomes. However, the presence of class imbalance within …
early diagnosis and treatment outcomes. However, the presence of class imbalance within …
[HTML][HTML] IoT and ensemble long-short-term-memory-based evapotranspiration forecasting for Riyadh
Evapotranspiration (ET) is the fundamental component of efficient water resource
management. Accurate forecasting of ET is essential for efficient water utilization in …
management. Accurate forecasting of ET is essential for efficient water utilization in …
Assessing the performance of deep learning models for colon polyp classification using computed tomography scans
the diagnosis of Colorectal and Rectum Cancer (CRC) is a global concern as it is the third
most commonly diagnosed cancer. Early detection and treatment of polyps can prevent the …
most commonly diagnosed cancer. Early detection and treatment of polyps can prevent the …
Enhancing early detection of COVID-19 with machine learning and blood test results
The medical community has a significant interest in an accurate, reliable, and effective
Medical Diagnosis Support System for COVID-19. Compared to the RT-PCR test, clinical …
Medical Diagnosis Support System for COVID-19. Compared to the RT-PCR test, clinical …
Healthcare embedded system for predicting Parkinson's Disease based on AI of things
This study aims to build a healthcare-embedded system based on the Artificial Intelligence
of Things (AIoT) to predict people affected by Parkinson's Disease (PD) via vocal disorders …
of Things (AIoT) to predict people affected by Parkinson's Disease (PD) via vocal disorders …
Exploring machine learning approaches for breast cancer prediction: a comparative analysis with ANOVA-based feature selection
K Boutahar, S Laghmati, H Moujahid… - … Research in Applied …, 2024 - ieeexplore.ieee.org
A widespread issue across the globe, breast cancer impacts women across diverse regions
and populations. Early detection remains crucial for improving treatment outcomes and …
and populations. Early detection remains crucial for improving treatment outcomes and …