A Semi-Automated Solution Approach Selection Tool for Any Use Case via Scopus and OpenAI: a Case Study for AI/ML in Oncology

Research output: Working paper/PreprintPreprint

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Abstract

In today's vast literature landscape, a manual review is very time-consuming. To address this challenge, this paper proposes a semi-automated tool for solution method review and selection. It caters to researchers, practitioners, and decision-makers while serving as a benchmark for future work. The tool comprises three modules: (1) paper selection and scoring, using a keyword selection scheme to query Scopus API and compute relevancy; (2) solution method extraction in papers utilizing OpenAI API; (3) sensitivity analysis and post-analyzes. It reveals trends, relevant papers, and methods. AI in the oncology case study and several use cases are presented with promising results, comparing the tool to manual ground truth.
Original languageEnglish
PublisherarXiv
Number of pages62
DOIs
Publication statusPublished - 10 Jul 2023

Bibliographical note

The paper is under review in Expert Systems with Applications, Elsevier

Keywords

  • cs.AI
  • cs.IR
  • cs.LG

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