Browse Articles

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 how injuries sustained during water tubing, that require treatment at an emergency department, differ between males and females.

The authors use blood smears from individuals with sickle cell disease to correlate sickle cell frequency with the occurrence of vaso-occlusive crises.

The authors looked at public knowledge regarding suggested daily limits for sugar intake and then looked at how sugar levels vary in the same drink obtained from different sources and across different days.

The authors created a 1D model to diagnose hepatomegaly and cirrhosis via ultrasound of the liver.

This study investigated how well food labels from 280 different brands across multiple food and drink categories in India and the US adhered to recommended nutritional labeling standards as outlined by the Codex Alimentarius.

The authors looked at the ability of different deep learning models to predict the presence of lung cancer from chest CT scans. They found that a pre-trained CNN model performed better than an autoencoder model.

This study compares the performance of two deep learning models, U-Net and DeconvNet, for segmenting gliomas from MRI scans.

Arrhythmias vary in type and treatment, and ECGs are used to detect them, though human interpretation can be inconsistent. The researchers tested four tree-based algorithms (gradient boosting, random forest, decision tree, and extra trees) on ECG data from over 10,000 patients.