Artificial intelligence (AI) and internet of medical things (IoMT) assisted biomedical systems for intelligent healthcare
Artificial intelligence (AI) is a modern approach based on computer science that develops
programs and algorithms to make devices intelligent and efficient for performing tasks that …
programs and algorithms to make devices intelligent and efficient for performing tasks that …
Advances in data preprocessing for biomedical data fusion: An overview of the methods, challenges, and prospects
Due to the proliferation of biomedical imaging modalities, such as Photoacoustic
Tomography, Computed Tomography (CT), Optical Microscopy and Tomography, etc …
Tomography, Computed Tomography (CT), Optical Microscopy and Tomography, etc …
Artificial intelligence in healthcare: past, present and future
Artificial intelligence (AI) aims to mimic human cognitive functions. It is bringing a paradigm
shift to healthcare, powered by increasing availability of healthcare data and rapid progress …
shift to healthcare, powered by increasing availability of healthcare data and rapid progress …
A transfer learning approach for early diagnosis of Alzheimer's disease on MRI images
Mild cognitive impairment (MCI) detection using magnetic resonance image (MRI), plays a
crucial role in the treatment of dementia disease at an early stage. Deep learning …
crucial role in the treatment of dementia disease at an early stage. Deep learning …
Prediction of Alzheimer's Disease Using DHO‐Based Pretrained CNN Model
S Venkatasubramanian, JN Dwivedi… - Mathematical …, 2023 - Wiley Online Library
Detecting Alzheimer's disease (AD) early on allows patients to take preventative measures
before the onset of irreversible brain damage, which is a critical factor in the treatment of …
before the onset of irreversible brain damage, which is a critical factor in the treatment of …
Notice of retraction: AI techniques for COVID-19
AA Hussain, O Bouachir, F Al-Turjman… - IEEE access, 2020 - ieeexplore.ieee.org
Notice of Retraction "AI Techniques for COVID-19," by Adedoyin Ahmed Hussain; Ouns
Bouachir; Fadi Al-Turjman; Moayad A Page 1 Notice of Retraction "AI Techniques for COVID-19," …
Bouachir; Fadi Al-Turjman; Moayad A Page 1 Notice of Retraction "AI Techniques for COVID-19," …
Conventional machine learning and deep learning in Alzheimer's disease diagnosis using neuroimaging: A review
Alzheimer's disease (AD) is a neurodegenerative disorder that causes memory degradation
and cognitive function impairment in elderly people. The irreversible and devastating …
and cognitive function impairment in elderly people. The irreversible and devastating …
Studying the manifold structure of Alzheimer's disease: a deep learning approach using convolutional autoencoders
Many classical machine learning techniques have been used to explore Alzheimer's
disease (AD), evolving from image decomposition techniques such as principal component …
disease (AD), evolving from image decomposition techniques such as principal component …
Classification of Alzheimer's disease using ensemble of deep neural networks trained through transfer learning
Alzheimer's disease (AD) is one of the deadliest neurodegenerative diseases ailing the
elderly population all over the world. An ensemble of Deep learning (DL) models can learn …
elderly population all over the world. An ensemble of Deep learning (DL) models can learn …
[PDF][PDF] Applications of Artificial Intelligence in Medical Devices and Healthcare
SS Gadde, VDR Kalli - … Journal of Computer Science Trends and …, 2020 - researchgate.net
Artificial intelligence (AI) can detect significant data set interactions and is commonly used
for the expectation of outcomes, treatment, and diagnosis in several clinical conditions. For a …
for the expectation of outcomes, treatment, and diagnosis in several clinical conditions. For a …