BP301T · Semester 3 · B.Pharm
Unit II — Regression Models in Healthcare
Introduction to Machine Learning in Pharmaceutical Sciences
This study page introduces Regression Models in Healthcare in Introduction to Machine Learning in Pharmaceutical Sciences (BP301T), B.Pharm Semester 3. Read the selected definitions and short notes below, then download the full unit PDF.
Topics in this unit
- Linear and multiple linear regression
- Model coefficients, residuals, and goodness-of-fit
- MSE, RMSE, and R²
- Fictional dose-response, dissolution-rate, PK-parameter, and sklearn predictive-model demonstrations
Definitions and short notes
Selected extracts from this unit’s notes. Download the full PDF below for the remaining topics and examples.
Regression
Regression is a supervised learning method that predicts a continuous numerical answer — any number on a scale, such as 62.5% dissolution, 4.2 hours half-life, or 120 mg dose requirement. "Continuous" means the answer can be any value, not just fixed categories.
Unit PDF · page 2
Predictive modeling
Predictive modeling means building a mathematical model from past data so it can predict future values. A regression equation built from past dissolution tests that predicts tomorrow's batch result is a predictive model.
Unit PDF · page 2
Download notes
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For education and exam preparation only, not medical advice or current regulatory guidance.