Latest AI and machine learning research in geriatrics for healthcare professionals.
Balances in the energy sector have changed since the implementation of the Covid-19 pandemic lockdown in Europe. This paper analyses how the lockdown affected electricity generation in European countries and how it will reshape future energy generation. Monthly electricity generation from total renewables and non-renewables in France, Germany, Spain, Turkey, and the UK from January 2017 to Septemb...
Emotion recognition is an important research field for human-computer interaction. Audio-video emotion recognition is now attacked with deep neural network modeling tools. In published papers, as a rule, the authors show only cases of the superiority in multi-modality over audio-only or video-only modality. However, there are cases of superiority in uni-modality that can be found. In our research,...
Aging is universal, yet characterizing the molecular changes that occur in aging which lead to an increased risk for neurological disease remains a ch...
The use of artificial intelligence (AI) in healthcare comes with opportunities but also numerous challenges. A specific challenge that remains underex...
OBJECTIVE: The role of deep learning-based echocardiography in the diagnosis and evaluation of the effects of routine anti-heart-failure Western medic...
Due to the large number of elderly people with physical and cognitive issues, there is a strong need to provide indoor location systems that help care...
Smuggling of drugs and cigarettes in small inflatable boats across border rivers is a serious threat to the EU's financial interests. Early detection ...
Orthognathic surgical outcomes rely heavily on the quality of surgical planning. Automatic estimation of a reference facial bone shape significantly r...
Normative modelling is an emerging method for quantifying how individuals deviate from the healthy populational pattern. Several machine learning mode...
BACKGROUND: Mild cognitive impairment (MCI) is a stage preceding dementia, and early intervention is critical. This study investigated whether multi-d...
Studies of structural connectivity at the synaptic level show that in synaptic connections of the cerebral cortex, the excitatory postsynaptic potenti...
Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that causes coronavirus disease 2019 (COVID-19) commonly presents with pne...
Robot-assisted hand training adopting end-effector devices results in an additional reduction of motor impairment in comparison to usual care alone in...
PURPOSE: The purpose of this study is to develop and validate a 3D deep learning model that predicts the final clinical diagnosis of Alzheimer's disea...
In Alzheimer's disease (AD), the contribution of pathophysiological mechanisms other than amyloidosis and tauopathy is now widely recognized, although...
The neural network algorithm of deep learning was applied to optimize and improve color Doppler ultrasound images, which was used for the research on ...
This article presents the hardware-software design and implementation of an open, integrated, and scalable healthcare platform oriented to multiple po...
A growing body of evidence currently proposes that deep learning approaches can serve as an essential cornerstone for the diagnosis and prediction of ...
Disruptive innovation is an invention that disrupts an existing market and creates a new one by providing a different set of values, which ultimately ...
To develop an efficient, embedded electroencephalogram (EEG) channel selection approach for deep neural networks, allowing us to match the channel sel...