Machine learning in arrhythmia and electrophysiology
Machine learning (ML), a branch of artificial intelligence, where machines learn from big
data, is at the crest of a technological wave of change swee** society. Cardiovascular …
data, is at the crest of a technological wave of change swee** society. Cardiovascular …
Scalably nanomanufactured atomically thin materials‐based wearable health sensors
Wearable multimodal sensors could enable the continuous, non‐invasive, precise
monitoring of vital human signals critical for remote health monitoring and telemedicine …
monitoring of vital human signals critical for remote health monitoring and telemedicine …
Parkinson's disease severity clustering based on tap** activity on mobile device
In this study, we investigated the relationship between finger tap** tasks on the
smartphone and the MDS-UPDRS I–II and PDQ-8 using the mPower dataset. mPower is a …
smartphone and the MDS-UPDRS I–II and PDQ-8 using the mPower dataset. mPower is a …
Deep learning algorithm of 12-lead electrocardiogram for Parkinson disease screening
H Yoo, SH Chung, CN Lee… - Journal of Parkinson's …, 2023 - content.iospress.com
Background: Although idiopathic Parkinson's disease (IPD) is increasing with the aging
population, there is no adequate screening test for early diagnosis of IPD. Cardiac …
population, there is no adequate screening test for early diagnosis of IPD. Cardiac …
Chronotropic incompetence during exercise testing as a marker of autonomic dysfunction in individuals with early Parkinson's disease
Background: An attenuated heart rate response to exercise, termed chronotropic
incompetence, has been reported in Parkinson's disease (PD). Chronotropic incompetence …
incompetence, has been reported in Parkinson's disease (PD). Chronotropic incompetence …
Predicting Parkinson's disease and its pathology via simple clinical variables
Background: Parkinson's disease (PD) is a chronic, disabling neurodegenerative disorder.
Objective: To predict a future diagnosis of PD using questionnaires and simple non-invasive …
Objective: To predict a future diagnosis of PD using questionnaires and simple non-invasive …
Autonomic function in Parkinson's disease subjects across repeated short-term dry immersion: Evidence from linear and non-linear hrv parameters
Several studies have shown that “dry” immersion appears as a promising method of
rehabilitation for Parkinson's disease. Still, little is known about the cardiovascular reaction …
rehabilitation for Parkinson's disease. Still, little is known about the cardiovascular reaction …
[HTML][HTML] Artificial intelligence–assisted prediction of late-onset cardiomyopathy among childhood cancer survivors
PURPOSE Early identification of childhood cancer survivors at high risk for treatment-related
cardiomyopathy may improve outcomes by enabling intervention before development of …
cardiomyopathy may improve outcomes by enabling intervention before development of …
Multimodal biofeedback for Parkinson's disease motor and nonmotor symptoms
Z Shi, L Ding, X Han, B Jiang, J Zhang… - Brain Science …, 2023 - journals.sagepub.com
Parkinson's disease (PD) is a neurodegenerative disorder characterized by motor
retardation, myotonia, quiescent tremor, and postural gait abnormality, as well as nonmotor …
retardation, myotonia, quiescent tremor, and postural gait abnormality, as well as nonmotor …
Diagnosing Parkinson's disease using multimodal physiological signals
G Guo, S Wang, S Wang, Z Zhou, G Pei… - Human Brain and Artificial …, 2021 - Springer
Parkinson's disease (PD) is the second most common neurodegenerative disease after
Alzheimer's disease. Due to the complex etiology and diverse clinical symptoms, it's difficult …
Alzheimer's disease. Due to the complex etiology and diverse clinical symptoms, it's difficult …