The authors created a 1D model to diagnose hepatomegaly and cirrhosis via ultrasound of the liver.
Read More...A 1D model of ultrasound waves for diagnosing of hepatomegaly and cirrhosis
The authors created a 1D model to diagnose hepatomegaly and cirrhosis via ultrasound of the liver.
Read More...A comparative analysis of machine learning approaches to predict brain tumors using MRI
The authors use machine learning on MRI images of brain tissue to predict tumor onset as an avenue for early detection of brain cancer.
Read More...Predictions of neural control deficits in elders with subjective memory complaints and Alzheimer’s disease
The authors compare neuroimaging datasets to identify potential new biomarkers for earlier detection of Alzheimer's disease.
Read More...A novel approach for predicting Alzheimer’s disease using machine learning on DNA methylation in blood
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%.
Read More...Distribution of prophages in the Streptococcus bacteria genus and their role in increasing host pathogenicity
The authors investigated prophages present in Streptococcus bacteria that may increase their survival in different environments.
Read More...A novel bioreactor system to purify contaminated runoff water
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.
Read More...DyGS: A Dynamic Gene Searching Algorithm for Cancer Detection
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.
Read More...Optimizing Arthrospira platensis growth for biofuel production via symbiosis between cyanobacteria strains
The authors test symbiotic relationships among cyanobacteria species to generate more robust cultures for potential biofuel production.
Read More...Predicting sickle cell vaso-occlusion by microscopic imaging and modeling
The authors use blood smears from individuals with sickle cell disease to correlate sickle cell frequency with the occurrence of vaso-occlusive crises.
Read More...Using advanced machine learning and voice analysis features for Parkinson’s disease progression prediction
The authors looked at the ability to use audio clips to analyze the progression of Parkinson's disease.
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