Machine-learning model helps detect diabetic patients at risk for kidney damage

In this study, the company reported that the algorithm identified 45% of patients who experienced significant kidney damage within one year – 25% more patients than commonly-used clinical tools would have detected, according to Medial EarlySign. Get the full story at our sister site, Drug Delivery Business News. The post Machine-learning model helps detect diabetic patients at risk for kidney damage appeared first on MassDevice.
Source: Mass Device - Category: Medical Devices Authors: Tags: Diabetes Diagnostics Hospital Care mHealth (Mobile Health) Software / IT medialearlysign Source Type: news

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This study indicates that frailty and other age-related diseases could be prevented and significantly reduced in older adults. Getting our heart risk factors under control could lead to much healthier old ages. Unfortunately, the current obesity epidemic is moving the older population in the wrong direction, however our study underlines how even small reductions in risk are worthwhile." The study analysed data from more than 421,000 people aged 60-69 in both GP medical records and in the UK Biobank research study. Participants were followed up over ten years. The researchers analysed six factors that could impa...
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This article published in 2015 discusses some of the negative issues that have been associated with sitting including: Impeded cardiovascular and metabolic function Depression and psychological distress (for example, a “mental funk”) Spike in blood sugar levels Increased risk for heart attack, type 2 diabetes, insomnia, arthritis, certain types of cancers, and premature death As you can see, this list is comprised of serious issues, and the author of the article gives some great suggestions for reducing your time sitting as well as for combating sitting’s negative effects. It is interesting to note tha...
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