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A machine learning approach for abstraction and reasoning problems without large amounts of data

Isik et al. | Jun 25, 2022

A machine learning approach for abstraction and reasoning problems without large amounts of data

While remarkable in its ability to mirror human cognition, machine learning and its associated algorithms often require extensive data to prove effective in completing tasks. However, data is not always plentiful, with unpredictable events occurring throughout our daily lives that require flexibility by artificial intelligence utilized in technology such as personal assistants and self-driving vehicles. Driven by the need for AI to complete tasks without extensive training, the researchers in this article use fluid intelligence assessments to develop an algorithm capable of generalization and abstraction. By forgoing prioritization on skill-based training, this article demonstrates the potential of focusing on a more generalized cognitive ability for artificial intelligence, proving more flexible and thus human-like in solving unique tasks than skill-focused algorithms.

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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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Herbal Extracts Alter Amyloid Beta Levels in SH-SY5Y Neuroblastoma Cells

Xu et al. | Feb 25, 2020

Herbal Extracts Alter Amyloid Beta Levels in SH-SY5Y Neuroblastoma Cells

Alzheimer’s disease (AD) is a type of dementia that affects more than 5.5 million Americans, and there are no approved treatments that can delay the advancement of the disease. In this work, Xu and Mitchell test the effects of various herbal extracts (bugleweed, hops, sassafras, and white camphor) on Aβ1-40 peptide levels in human neuroblastoma cells. Their results suggest that bugleweed may have the potential to reduce Aβ1-40 levels through its anti-inflammatory properties.

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