[HTML][HTML] Applications of artificial intelligence to obesity research: scoping review of methodologies

R An, J Shen, Y Xiao - Journal of Medical Internet Research, 2022 - jmir.org
Background Obesity is a leading cause of preventable death worldwide. Artificial
intelligence (AI), characterized by machine learning (ML) and deep learning (DL), has …

A review of the application of deep learning in obesity: From early prediction aid to advanced management assistance

X Yi, Z Heyang, S Gao, M Li - … & Metabolic Syndrome: Clinical Research & …, 2024 - Elsevier
Background and aims Obesity is a chronic disease which can cause severe metabolic
disorders. Machine learning (ML) techniques, especially deep learning (DL), have proven to …

[HTML][HTML] A novel few-shot classification framework for diabetic retinopathy detection and grading

M Murugappan, NB Prakash, R Jeya… - Measurement, 2022 - Elsevier
Diabetes Retinopathy (DR) is a major microvascular complication of diabetes. Computer-
Aided Diagnosis (CAD) tools for DR management are primarily developed using Artificial …

Tongue image fusion and analysis of thermal and visible images in diabetes mellitus using machine learning techniques

U Thirunavukkarasu, S Umapathy, V Ravi… - Scientific Reports, 2024 - nature.com
The study aimed to achieve the following objectives:(1) to perform the fusion of thermal and
visible tongue images with various fusion rules of discrete wavelet transform (DWT) to …

Deep learning techniques for automated detection of autism spectrum disorder based on thermal imaging

K Ganesh, S Umapathy… - Proceedings of the …, 2021 - journals.sagepub.com
Children with autism spectrum disorder have impairments in emotional processing which
leads to the inability in recognizing facial expressions. Since emotion is a vital criterion for …

[HTML][HTML] Explainable artificial intelligence for investigating the effect of lifestyle factors on obesity

T Khater, H Tawfik, B Singh - Intelligent Systems with Applications, 2024 - Elsevier
Obesity is a critical health issue associated with severe medical conditions. To enhance
public health and well-being, early prediction of obesity risk is crucial. This study introduces …

Fat-based studies for computer-assisted screening of child obesity using thermal imaging based on deep learning techniques: a comparison with quantum machine …

R Rashmi, U Snekhalatha, PT Krishnan, V Dhanraj - Soft Computing, 2023 - Springer
The main objectives are (i) to study the relation of temperature of brown adipose tissue
(BAT) with respect to obesity in different regions of the human body and to predict the most …

[HTML][HTML] Comprehensive Data Augmentation Approach Using WGAN-GP and UMAP for Enhancing Alzheimer's Disease Diagnosis

E Yuda, T Ando, I Kaneko, Y Yoshida, D Hirahara - Electronics, 2024 - mdpi.com
In this study, the Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-
GP) was used to improve the diagnosis of Alzheimer's disease using medical imaging and …

Deep transfer learning-based fall detection approach using IoMT-enabled thermal imaging-assisted pervasive surveillance and big health data

K Rezaee, MR Khosravi, N Neshat… - Journal of Circuits …, 2022 - World Scientific
People's need for healthcare capacity has become increasingly critical as the elderly
population continues to grow in most communities. Approximately 25–47% of seniors fall …

Convolutional neural network-based computer-aided diagnosis in Hiesho (cold sensation)

T Wang, M Endo, Y Ohno, S Okada… - Computers in Biology and …, 2022 - Elsevier
Hiesho (cold sensation) is a worldwide health problem primarily occurring in women.
Females who suffered from Hiesho reported cold feeling at the extremities, which was also …