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

Deniz Kenan Kılıç; Alex Elkjær Vasegaard; Aurélien Desoeuvres; Peter Nielsen

doi:10.48550/arXiv.2307.04573

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

Deniz Kenan Kılıç^*
, Alex Elkjær Vasegaard
, Aurélien Desoeuvres
, Peter Nielsen

^*Corresponding author for this work

Research output: Working paper/Preprint › Preprint

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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 language	English
Publisher	arXiv
Number of pages	62
DOIs	https://doi.org/10.48550/arXiv.2307.04573
Publication status	Published - 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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10.48550/arXiv.2307.04573Licence: CC BY-NC-ND 4.0

2307.04573v1Final published version, 1.34 MBLicence: CC BY-NC-ND 4.0

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@misc{f997799da0604413851fe20e0f21f7ca,

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

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. ",

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author = "Kılı{\c c}, \{Deniz Kenan\} and Vasegaard, \{Alex Elkj{\ae}r\} and Aur{\'e}lien Desoeuvres and Peter Nielsen",

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

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month = jul,

day = "10",

doi = "10.48550/arXiv.2307.04573",

language = "English",

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AU - Desoeuvres, Aurélien

AU - Nielsen, Peter

N1 - The paper is under review in Expert Systems with Applications, Elsevier

PY - 2023/7/10

Y1 - 2023/7/10

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AB - 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.

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KW - cs.IR

KW - cs.LG

U2 - 10.48550/arXiv.2307.04573

DO - 10.48550/arXiv.2307.04573

M3 - Preprint

BT - A Semi-Automated Solution Approach Selection Tool for Any Use Case via Scopus and OpenAI

PB - arXiv

ER -

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

Abstract

Bibliographical note

Keywords

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