Automatically extracting, ranking and visually summarizing the treatments for a disease

TL;DR

This paper presents an automated approach to extract, rank, and visually summarize treatment options for diseases using Medline abstracts, aiding clinicians in quickly accessing relevant treatment information.

Contribution

The study introduces a method to automatically identify and rank treatments from biomedical literature, providing concise summaries for clinicians.

Findings

Achieved maximum F-score of 0.611 for Atrial Fibrillation treatments

Achieved maximum F-score of 0.503 for Congestive Heart Failure treatments

Effectively ranked treatments to assist clinical decision-making

Abstract

Clinicians are expected to have up-to-date and broad knowledge of disease treatment options for a patient. Online health knowledge resources contain a wealth of information. However, because of the time investment needed to disseminate and rank pertinent information, there is a need to summarize the information in a more concise format. Our aim of the study is to provide clinicians with a concise overview of popular treatments for a given disease using information automatically computed from Medline abstracts. We analyzed the treatments of two disorders - Atrial Fibrillation and Congestive Heart Failure. We calculated the precision, recall, and f-scores of our two ranking methods to measure the accuracy of the results. For Atrial Fibrillation disorder, maximum f-score for the New Treatments weighing method is 0.611, which occurs at 60 treatments. For Congestive Heart Failure disorder, maximum f-score for the New Treatments weighing method is 0.503, which occurs at 80 treatments.