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The authors looked at how vocabulary is impacted in Alzheimer's disease and whether it could be used a predictor of disease onset.

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

The authors use machine learning on MRI images of brain tissue to predict tumor onset as an avenue for early detection of brain cancer.

The authors compare neuroimaging datasets to identify potential new biomarkers for earlier detection of Alzheimer's disease.

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%.

In this study, the authors engineer a cost-effective and bio-friendly water purification system using limestone, denitrifying bacteria, and sulfate-reducing bacteria. They evaluated its efficacy with samples from Eastern PA industrial sites.

Wang and Gong developed a novel dynamic gene-searching algorithm called Dynamic Gene Search (DyGS) to create a gene panel for each of the 12 cancers with the highest annual incidence and death rate. The 12 gene panels the DyGS algorithm selected used only 3.5% of the original gene mutation pool, while covering every patient sample. About 40% of each gene panel is druggable, which indicates that the DyGS-generated gene panels can be used for early cancer detection as well as therapeutic targets in treatment methods.

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 the ability to use audio clips to analyze the progression of Parkinson's disease.

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