[HTML][HTML] The role of artificial intelligence in early cancer diagnosis

B Hunter, S Hindocha, RW Lee - Cancers, 2022 - mdpi.com
Simple Summary Diagnosing cancer at an early stage increases the chance of performing
effective treatment in many tumour groups. Key approaches include screening patients who …

[HTML][HTML] Machine learning on thyroid disease: a review

KS Lee, H Park - Frontiers in Bioscience-Landmark, 2022 - imrpress.com
This study reviews the recent progress of machine learning for the early diagnosis of thyroid
disease. Based on the results of this review, different machine learning methods would be …

[HTML][HTML] A real-time computer vision based approach to detection and classification of traffic incidents

MI Basheer Ahmed, R Zaghdoud, MS Ahmed… - Big data and cognitive …, 2023 - mdpi.com
To constructively ameliorate and enhance traffic safety measures in Saudi Arabia, a prolific
number of AI (Artificial Intelligence) traffic surveillance technologies have emerged …

Time-frequency analysis of speech signal using Chirplet transform for automatic diagnosis of Parkinson's disease

P Warule, SP Mishra, S Deb - Biomedical Engineering Letters, 2023 - Springer
Parkinson's disease (PD) is the second most prevalent neurodegenerative disorder in the
world after Alzheimer's disease. Early diagnosing PD is challenging as it evolved slowly …

[HTML][HTML] Prediction of generalized anxiety levels during the Covid-19 pandemic: A machine learning-based modeling approach

FM Albagmi, A Alansari, DS Al Shawan… - Informatics in Medicine …, 2022 - Elsevier
The rapid spread of the Covid-19 outbreak led many countries to enforce precautionary
measures such as complete lockdowns. These lifestyle-altering measures caused a …

[HTML][HTML] Ensemble learning-based investigation of thermal conductivity of Bi2Te2. 7Se0. 3-based thermoelectric clean energy materials

YS Wudil - Results in Engineering, 2023 - Elsevier
Bi 2 Te 3-based materials are remarkable semiconducting compounds widely employed for
clean energy harvesting via thermoelectric effects. Their energy conversion efficiency is …

Predicting the thermal conductivity of Bi2Te3-based thermoelectric energy materials: A machine learning approach

TA Alrebdi, YS Wudil, UF Ahmad, FA Yakasai… - International Journal of …, 2022 - Elsevier
Bi 2 Te 3-based materials are remarkable thermoelectric renewable energy harvesters. The
measurement of their thermal conductivity (κ) is a critical phase toward the realization of the …

A multi-channel deep convolutional neural network for multi-classifying thyroid diseases

X Zhang, VCS Lee, J Rong, JC Lee, J Song… - Computers in Biology and …, 2022 - Elsevier
Abstract Background and Objective: Thyroid disease instances have been continuously
increasing since the 1990s, and thyroid cancer has become the most rapidly rising disease …

Preemptive diagnosis of Alzheimer's disease in the eastern province of Saudi Arabia using computational intelligence techniques

SO Olatunji, A Alansari, H Alkhorasani… - Computational …, 2022 - Wiley Online Library
Alzheimer's Disease (AD) is a silent disease that causes the brain cells to die progressively,
influencing consciousness, behavior, planning ability, and language to name a few. AD …

[HTML][HTML] Computer-aided diagnosis systems: a comparative study of classical machine learning versus deep learning-based approaches

R Guetari, H Ayari, H Sakly - Knowledge and Information Systems, 2023 - Springer
The diagnostic phase of the treatment process is essential for patient guidance and follow-
up. The accuracy and effectiveness of this phase can determine the life or death of a patient …