Using Supervised Learning Methods to Develop a List of Prescription Medications of Greatest Concern during Pregnancy.

ABSTRACT:

Introduction

Women and healthcare providers lack adequate information on medication safety during pregnancy. While resources describing fetal risk are available, information is provided in multiple locations, often with subjective assessments of available data. We developed a list of medications of greatest concern during pregnancy to help healthcare providers counsel reproductive-aged and pregnant women.

Methods

Prescription drug labels submitted to the U.S. Food and Drug Administration with information in the Teratogen Information System (TERIS) and/or Drugs in Pregnancy and Lactation by Briggs & Freeman were included (N = 1,186 medications; 766 from three data sources, 420 from two). We used two supervised learning methods ('support vector machine' and 'sentiment analysis

SUBMITTER: Ailes EC 

PROVIDER: S-EPMC7482428 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature