Cancer patients are prescribed with different drugs. There is a great interest in providing tools for the doctors to analyze which drugs have the highest impact In different tests results (i.e., White Blood Count, Red Blood Count, Hemoglobin, etc.).
Compared test results before and after the treatment. Since data were indexed by time (time series) different techniques (e.g., interpolation, averaging, etc.) were used to estimate values before and after treatment. Computed absolute change, relative change, and the density function for the variation of each test result and visualized it, showing clear differences across drugs. Also allowed to visualize changes in different test results as treatment progresses for each patient.
- Data Science Experience
Data Science Techniques
- Visualization, regression, time series interpolation
By finding out the tests presenting highest variation, specialists can better understand the effects of drugs on different patients, as well more accurately prescribe a drug for a patient with specific conditions determined by their test results.
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