Artificial intelligence in andrology: from semen analysis to image diagnostics
R Abou Ghayda, R Cannarella… - The World Journal …, 2023 - pmc.ncbi.nlm.nih.gov
Artificial intelligence (AI) in medicine has gained a lot of momentum in the last decades and
has been applied to various fields of medicine. Advances in computer science, medical …
has been applied to various fields of medicine. Advances in computer science, medical …
Meta-health: learning-to-learn (Meta-learning) as a next generation of deep learning exploring healthcare challenges and solutions for rare disorders: a systematic …
In clinical scenarios, the two subfields of Artificial Intelligence (AI), ie, Machine Learning (ML)
and Deep Learning (DL) methods have become the de facto standard in several domains of …
and Deep Learning (DL) methods have become the de facto standard in several domains of …
Improving structural MRI preprocessing with hybrid transformer GANs
Magnetic resonance imaging (MRI) is a technique that is widely used in practice to evaluate
any pathologies in the human body. One of the areas of interest is the human brain …
any pathologies in the human body. One of the areas of interest is the human brain …
Investigating the potential of reinforcement learning and deep learning in improving Alzheimer's disease classification
Alzheimer's disease (AD) is a progressive neurological disease that affects millions of
people worldwide, highlighting the importance of early and accurate diagnosis for effective …
people worldwide, highlighting the importance of early and accurate diagnosis for effective …
[HTML][HTML] A comparative study of GNN and MLP based machine learning for the diagnosis of Alzheimer's Disease involving data synthesis
Alzheimer's Disease (AD) is a neurodegenerative disease that commonly occurs in older
people. It is characterized by both cognitive and functional impairment. However, as AD has …
people. It is characterized by both cognitive and functional impairment. However, as AD has …
A review of the application of three-dimensional convolutional neural networks for the diagnosis of Alzheimer's disease using neuroimaging
X Xu, L Lin, S Sun, S Wu - Reviews in the Neurosciences, 2023 - degruyter.com
Alzheimer's disease (AD) is a degenerative disorder that leads to progressive, irreversible
cognitive decline. To obtain an accurate and timely diagnosis and detect AD at an early …
cognitive decline. To obtain an accurate and timely diagnosis and detect AD at an early …
Fecnet: A neural network and a mobile app for covid-19 recognition
Abstract COVID-19 has caused over 6.35 million deaths and over 555 million confirmed
cases till 11/July/2022. It has caused a serious impact on individual health, social and …
cases till 11/July/2022. It has caused a serious impact on individual health, social and …
Smart solutions for detecting, predicting, monitoring, and managing dementia in the elderly: A survey
Dementia, a syndrome which is characterized by a decline in cognitive abilities such as
memory, thinking, behavior, and the ability to perform daily living activities, is prevalent in …
memory, thinking, behavior, and the ability to perform daily living activities, is prevalent in …
Improving machine learning with ensemble learning on observational healthcare data
B Naderalvojoud… - AMIA Annual …, 2024 - pmc.ncbi.nlm.nih.gov
Ensemble learning is a powerful technique for improving the accuracy and reliability of
prediction models, especially in scenarios where individual models may not perform well …
prediction models, especially in scenarios where individual models may not perform well …
Ensemble intelligence algorithms and soil environmental quality to model economic quantity of land resource allocation and spatial inequality
F Gao, S Yi, X Li, W Chen - Land Use Policy, 2024 - Elsevier
With the increasing concern on soil pollution in context of land market reform, it's an
emerging topic to discuss whether soil pollution can cause land economic value …
emerging topic to discuss whether soil pollution can cause land economic value …