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The authors used developed a machine learning tool for studying social media discourse surrounding use of tobacco and cannabis.

The authors looked at using computer vision to evaluate the degree of exotropia in individuals with strabismus.

This study analyzes genetic alterations and expression patterns of protein kinases involved in phagocytosis across multiple cancers using TCGA data.

The authors looked at common themes of videos created by 10 different dental influencers.

The authors assess incidence and mortality rates of two cancer types in relation to trihalomethane pollutant concentrations in drinking water.

The authors looked at different factors, such as age, pre-existing conditions, and geographic region, and their ability to predict what an individual's health insurance premium would be.

The authors looked at the correlation between being able to speak more than one language (multilingualism) and visual imagery. They found multilingual individuals had higher visual imagery as measured by the VVIQ.

Using machine learning to predict the risk of algae bloom

Lung cancer is highly fatal, largely due to late diagnoses, but early detection can greatly improve survival. This study developed three models to enhance early diagnosis: an MLP for clinical data, a CNN for imaging data, and a hybrid model combining both.

Default opt-ins and social proof tags effect on decision making in an e-commerce context