This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
Introduction:All-cause dementia remains a significant public health concern, with stroke recognized as a key riskfactor. Few studies have applied Machine Learning (ML) models to accurately predict cognitive impairment and dementia, yet none have specifically focused on post-stroke dementiarisk prediction.
Introduction:Stroke and dementia are among the leading causes of mortality globally. This can be mitigated through targeting modifiable riskfactors. Identification of those at-risk through screening tools could be facilitated by inclusion of self-reported riskfactors rather than reliance on clinical data.
It’s not that they don’t get cardiovascular disease, cancer or dementia; they just get it way later than everyone else. When broken down by disease category, cardiovascular disease, cancer, dementia, stroke, osteoarthritis, hypertension and stroke, the pattern is the same. Aggressively control the riskfactors.
The benefit of resistance training observed in observational studies is supported by controlled trials on resistance training, which demonstrate that this type of exercise reduces traditional and nontraditional CVD riskfactors. Of course, these benefits can also extend to individuals with a BMI in the normal range.
The benefit of resistance training observed in observational studies is supported by controlled trials on resistance training, which demonstrate that this type of exercise reduces traditional and nontraditional CVD riskfactors. Of course, these benefits can also extend to individuals with a BMI in the normal range.
Cardiovascular disease, cancer and dementia account for 60% of all deaths in the US. Yes, many external factors impact these factors, but ultimately, you have significant control over all of these. Let’s look at what happens to NCD risk when these riskfactors are optimised. These are NCD’s.
Accumulation of oxidative stress has been shown to trigger the initiation and progression of cognitive deficits, including mild cognitive impairment (MCI) and Alzheimers Dementia (AD).
We organize all of the trending information in your field so you don't have to. Join thousands of users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content