Figure 1. Workflow of data-driven methodology for pulmonary symptomology in hypertension using machine learning models from preprocessing and dictionary creation to storing tables in the database an analysis.

As a part of data cleaning, we were also challenged by multiple technical issues when combining drugs: (i) there were many drugs’ names that did not track a specific standard. (ii) Formulations of the same active ingredient with different generic or brand names for different routes of administration created confusion in collecting data (for instance, Revatio, Viagra, sildenafil, sildenafil citrate, APO sildenafil, sildenafil film-coated tablet, sildenafil citrate Aurobindo pharma, sildenafil Amneal Pharmaceuticals, Teva sildenafil, sildenafil Pfizer, sildenafil Greenstone, sildenafil Hormosan Filmtabletten, Revathio, sildenafil SUP, etc.). For this purpose, we combined drugs with or without salt, alcohol, etc. from different generic names and brand names.