Systems and methods for transforming and storing data from multiple studies

A method comprising:

• retrieving a plurality of study results, wherein each study result comprises a plurality of datapoints, and wherein each datapoint comprises a plurality of attributes;
• extracting a plurality of questions from the plurality of study results;
• converting the plurality of questions into questions in a standardized format;
• assigning one or more categories to each of the plurality of questions;
• determining a group of questions, of the plurality of questions, that have a same set of assigned categories;
• combining the group of questions;
• generating a final dataset by combining the plurality of study results;
• selecting a plurality of features in the final dataset;
• and
• training a machine learning algorithm (MLA) using the plurality of features.

A method for predicting treatment efficacy for a patient, the method comprising:

• training a machine learning algorithm (MLA) by:
• retrieving a plurality of study results corresponding to a plurality of treatments, wherein each study result comprises a plurality of datapoints, and wherein each datapoint comprises a plurality of attributes,
• extracting a plurality of questions from the plurality of study results,
• converting the plurality of questions into questions in a standardized format,
• assigning one or more categories to each of the plurality of questions,
• determining a group of questions, of the plurality of questions, that have a same set of assigned categories,
• combining the group of questions,
• generating a final dataset by combining the plurality of study results, and
• training the MLA using the final dataset;
• receiving questionnaire responses from the patient;
• inputting the questionnaire responses into the MLA;
• outputting, by the MLA, a predicted efficacy of each of the plurality of treatments;
• generating, based on the predicted efficacy of each of the plurality of treatments, an interface;
• and
• outputting for display the interface.