[HTML][HTML] Multi-modality approaches for medical support systems: A systematic review of the last decade
Healthcare traditionally relies on single-modality approaches, which limit the information
available for medical decisions. However, advancements in technology and the availability …
available for medical decisions. However, advancements in technology and the availability …
[HTML][HTML] A survey of multimodal information fusion for smart healthcare: Map** the journey from data to wisdom
Multimodal medical data fusion has emerged as a transformative approach in smart
healthcare, enabling a comprehensive understanding of patient health and personalized …
healthcare, enabling a comprehensive understanding of patient health and personalized …
Alzheimer's disease detection using deep learning on neuroimaging: a systematic review
Alzheimer's disease (AD) is a pressing global issue, demanding effective diagnostic
approaches. This systematic review surveys the recent literature (2018 onwards) to …
approaches. This systematic review surveys the recent literature (2018 onwards) to …
Prediction of Alzheimer's progression based on multimodal deep-learning-based fusion and visual explainability of time-series data
Alzheimer's disease (AD) is a neurological illness that causes cognitive impairment and has
no known treatment. The premise for delivering timely therapy is the early diagnosis of AD …
no known treatment. The premise for delivering timely therapy is the early diagnosis of AD …
Explainable machine learning models based on multimodal time-series data for the early detection of Parkinson's disease
Background and objectives Parkinson's Disease (PD) is a devastating chronic neurological
condition. Machine learning (ML) techniques have been used in the early prediction of PD …
condition. Machine learning (ML) techniques have been used in the early prediction of PD …
[HTML][HTML] Optimized stacking ensemble learning model for breast cancer detection and classification using machine learning
Breast cancer is the most frequently encountered medical hazard for women in their forties,
affecting one in every eight women. It is the greatest cause of death worldwide, and early …
affecting one in every eight women. It is the greatest cause of death worldwide, and early …
Deception detection with machine learning: A systematic review and statistical analysis
Several studies applying Machine Learning to deception detection have been published in
the last decade. A rich and complex set of settings, approaches, theories, and results is now …
the last decade. A rich and complex set of settings, approaches, theories, and results is now …
Trustworthy artificial intelligence in Alzheimer's disease: state of the art, opportunities, and challenges
Abstract Medical applications of Artificial Intelligence (AI) have consistently shown
remarkable performance in providing medical professionals and patients with support for …
remarkable performance in providing medical professionals and patients with support for …
Alzheimer's disease diagnosis from single and multimodal data using machine and deep learning models: Achievements and future directions
Alzheimer's Disease (AD) is the most prevalent and rapidly progressing neurodegenerative
disorder among the elderly and is a leading cause of dementia. AD results in significant …
disorder among the elderly and is a leading cause of dementia. AD results in significant …
[HTML][HTML] Tracking changes in chlorophyll-a concentration and turbidity in Nansi Lake using Sentinel-2 imagery: A novel machine learning approach
J Zhang, F Meng, P Fu, T **g, J Xu, X Yang - Ecological Informatics, 2024 - Elsevier
This study represents the first application of Sentinel-2 remote sensing imagery and model
fusion techniques to assess the chlorophyll-a (Chla) concentration and turbidity in Nansi …
fusion techniques to assess the chlorophyll-a (Chla) concentration and turbidity in Nansi …