Machine learning and deep learning approaches for brain disease diagnosis: principles and recent advances

P Khan, MF Kader, SMR Islam, AB Rahman… - Ieee …, 2021 - ieeexplore.ieee.org
Brain is the controlling center of our body. With the advent of time, newer and newer brain
diseases are being discovered. Thus, because of the variability of brain diseases, existing …

Wearable sensors in the diagnosis and study of Parkinson's disease symptoms: A systematic review

AC Albán-Cadena, F Villalba-Meneses… - Journal of Medical …, 2021 - Taylor & Francis
Nowadays, there are several diseases which affect different systems of the body, producing
changes in the correct functioning of the organism and the people lifestyles. One of them is …

Real-time detection of freezing of gait in Parkinson's disease using multi-head convolutional neural networks and a single inertial sensor

L Borzì, L Sigcha, D Rodríguez-Martín… - Artificial intelligence in …, 2023 - Elsevier
Background: Freezing of gait (FOG) is one of the most disabling symptoms of Parkinson's
disease (PD), contributing to poor quality of life and increased risk of falls. Wearable sensors …

Activity recognition in parkinson's patients from motion data using a cnn model trained by healthy subjects

S Davidashvilly, M Hssayeni, C Chi… - 2022 44th annual …, 2022 - ieeexplore.ieee.org
Physical activity recognition in patients with Parkinson's Disease (PwPD) is challenging due
to the lack of large-enough and good quality motion data for PwPD. A common approach to …

[HTML][HTML] Quantitative Transcranial Sonography Evaluation of Substantia Nigra Hyperechogenicity Is Useful for Predicting Levodopa-Induced Dyskinesia in Parkinson …

JH Yan, K Li, YL Ge, W Li, PZ Wang, H Jin… - Ultrasound in Medicine …, 2023 - Elsevier
Levodopa-induced dyskinesia (LID) is a common motor complication in Parkinson disease
(PD). Abnormal substantia nigra hyperechogenicity (SN+), detected by transcranial …

Dyskinesia Estimation of Imbalanced Data Using a Deep-Learning Model

MD Hssayeni, J Jimenez-Shahed… - 2022 44th Annual …, 2022 - ieeexplore.ieee.org
The collection of Parkinson's Disease (PD) time-series data usually results in imbalanced
and incomplete datasets due to the geometric distribution of PD complications' sever-ity …

Activity selection to distinguish healthy people from parkinson's disease patients using i-da

L Tao, X Wang, X Peng, P Yang, J Qi… - 2021 17th International …, 2021 - ieeexplore.ieee.org
With the aggravation of the population aging problem, Parkinson's disease (PD) and other
neurodegenerative diseases of the elderly are not only a medical problem but also an …

[PDF][PDF] Design, development and validation of an

C Carissimo - 2023 - iris.unicas.it
The sustainable development of the planet is one of the widely discussed topics on the
United Nations table: issues like protecting the environment and the rights and health of …

OO-LSTM: A trusted medical transfers prediction model with on-chain and off-chain data fusion

L Kong, X Song, Q Yin, Q Li - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
When the medical services surrounding patients cannot meet the needs of patients, transfer
treatment has become an unavoidable part in the current medical environment. Initially …

Deep Learning Regression Models for Limited Biomedical Time-Series Data

MD Hssayeni - 2022 - search.proquest.com
Time-series data in biomedical applications are gaining an increased interest to detect and
predict underlying diseases and estimate their severity, such as Parkinson's disease (PD) …