[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 …
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 …
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 …
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 …
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 …
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 …
Chronic kidney disease prediction using boosting techniques based on clinical parameters
Chronic kidney disease (CKD) has become a major global health crisis, causing millions of
yearly deaths. Predicting the possibility of a person being affected by the disease will allow …
yearly deaths. Predicting the possibility of a person being affected by the disease will allow …
[HTML][HTML] A Modified Bio-Inspired Optimizer with Capsule Network for Diagnosis of Alzheimer Disease
P Ganesan, GP Ramesh, C Puttamdappa… - Applied Sciences, 2024 - mdpi.com
Recently, Alzheimer's disease (AD) is one of the common neurodegenerative disorders,
which primarily occurs in old age. Structural magnetic resonance imaging (sMRI) is an …
which primarily occurs in old age. Structural magnetic resonance imaging (sMRI) is an …
Predicting microbe organisms using data of living micro forms of life and hybrid microbes classifier
Microbe organisms make up approximately 60% of the earth's living matter and the human
body is home to millions of microbe organisms. Microbes are microbial threats to health and …
body is home to millions of microbe organisms. Microbes are microbial threats to health and …