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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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A Novel Alzheimer's Disease Therapeutic Model: Attenuating Hyperphosphorylated Tau and Amyloid β (Aβ) Aggregates by Characterizing Antioxidative, Anti-Inflammatory, and Neuroprotective Properties of Natural Extracts

Pokkunuri et al. | Jul 25, 2022

A Novel Alzheimer's Disease Therapeutic Model: Attenuating Hyperphosphorylated Tau and Amyloid β (Aβ) Aggregates by Characterizing Antioxidative, Anti-Inflammatory, and Neuroprotective Properties of Natural Extracts

Oxidative damage and neuro-inflammation were the key pathways implicated in the pathogenesis of Alzheimer’s disease. In this study, 30 natural extracts from plant roots and leaves with extensive anti-inflammatory and anti-oxidative properties were consumed by Drosophila melanogaster. Several assays were performed to evaluate the efficacy of these combinational extracts on delaying the progression of Alzheimer’s disease. The experimental group showed increased motor activity, improved associative memory, and decreased lifespan decline relative to the control group.

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An explainable model for content moderation

Cao et al. | Aug 16, 2023

An explainable model for content moderation

The authors looked at the ability of machine learning algorithms to interpret language given their increasing use in moderating content on social media. Using an explainable model they were able to achieve 81% accuracy in detecting fake vs. real news based on language of posts alone.

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Risk assessment modeling for childhood stunting using automated machine learning and demographic analysis

Sirohi et al. | Sep 25, 2022

Risk assessment modeling for childhood stunting using automated machine learning and demographic analysis

Over the last few decades, childhood stunting has persisted as a major global challenge. This study hypothesized that TPTO (Tree-based Pipeline Optimization Tool), an AutoML (automated machine learning) tool, would outperform all pre-existing machine learning models and reveal the positive impact of economic prosperity, strong familial traits, and resource attainability on reducing stunting risk. Feature correlation plots revealed that maternal height, wealth indicators, and parental education were universally important features for determining stunting outcomes approximately two years after birth. These results help inform future research by highlighting how demographic, familial, and socio-economic conditions influence stunting and providing medical professionals with a deployable risk assessment tool for predicting childhood stunting.

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A novel approach for predicting Alzheimer’s disease using machine learning on DNA methylation in blood

Adami et al. | Sep 20, 2023

A novel approach for predicting Alzheimer’s disease using machine learning on DNA methylation in blood
Image credit: National Cancer Institute

Here, recognizing the difficulty associated with tracking the progression of dementia, the authors used machine learning models to predict between the presence of cognitive normalcy, mild cognitive impairment, and Alzheimer's Disease, based on blood DNA methylation levels, sex, and age. With four machine learning models and two dataset dimensionality reduction methods they achieved an accuracy of 53.33%.

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Artificial intelligence assisted violin performance learning

Zhang et al. | Aug 30, 2023

Artificial intelligence assisted violin performance learning
Image credit: Philip Myrtorp

In this study the authors looked at the ability of artificial intelligence to detect tempo, rhythm, and intonation of a piece played on violin. Technology such as this would allow for students to practice and get feedback without the need of a teacher.

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