Medical image segmentation, or not enough data?
The adoption of machine learning applications has continually gained momentum in recent years across multiple sectors....
Python versus R
If you’re looking to engineer data solutions for life sciences, you need to know about Python and R....
Precision Medicine Driven by Bioinformatics and AI
The 19th and 20th centuries saw milestone achievements in medicine. From the development of the “germ theory” to the first vaccine; from the first stethoscope to the first practical electrocardiograph....
Reproducibility with R
In order to analyze any dataset you need a process. If those data sets involve vast amounts of information, how do you always ensure that the same exact same processes are followed each time?...
SAS to R
There’s a switch that’s beginning to sweep across digital domains globally; it’s the transition from using the legacy-based SAS proprietary software to R, a newer, open source, free to use software environment....
Applying data science techniques to healthcare data
Diagnostics – machine learning can be used to detect microscopic anomalies in medical images that can’t be seen by radiologists....
The progression of data in the healthcare industry
The increasing adoption of electronic information systems by the healthcare industry is generating vast amounts of data from which data scientists can extract valuable information. ...
Diagnosing diabetes using machine learning
Diabetes is a chronic disease that occurs when a patient’s blood glucose is higher than the normal level....
Image processing in Python
Deep learning is a widely used technique that is renowned for its high accuracy. It can be used in various fields such as regression/classification, image processing, and natural language processing....
