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A HOG feature extraction and CNN approach to Parkinson’s spiral drawing diagnosis

Tripathi et al. | Aug 09, 2024

A HOG feature extraction and CNN approach to Parkinson’s spiral drawing diagnosis

Parkinson’s disease (PD) is a prevalent neurodegenerative disorder in the U.S., second only to Alzheimer’s disease. Current diagnostic methods are often inefficient and dependent on clinical exams. This study explored using machine and deep learning to enhance PD diagnosis by analyzing spiral drawings affected by hand tremors, a common PD symptom.

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Using Artificial Intelligence to Forecast Continuous Glucose Monitor(CGM) readings for Type One Diabetes

Jalla et al. | Aug 07, 2024

Using Artificial Intelligence to Forecast Continuous Glucose Monitor(CGM) readings for Type One Diabetes
Image credit: The authors

People with Type One diabetes often rely on Continuous Blood Glucose Monitors (CGMs) to track their blood glucose and manage their condition. Researchers are now working to help people with Type One diabetes more easily monitor their health by developing models that will future blood glucose levels based on CGM readings. Jalla and Ghanta tackle this issue by exploring the use of AI models to forecast blood glucose levels with CGM data.

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Association between nonpharmacological interventions and dementia: A retrospective cohort study

Yerabandi et al. | Jan 09, 2023

Association between nonpharmacological interventions and dementia: A retrospective cohort study
Image credit: Ross Sneddon

Here, the authors investigated the role of nonpharmacological interventions in preventing or delaying cognitive impairment in individuals with and without dementia. By using a retrospective case-control study of 22 participants across two senior centers in San Diego, they found no significant differences in self-reported activities. However, they found that their results reflected activity rather than the activity itself, suggesting the need for an alternative type of study.

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