التفاصيل البيبلوغرافية
| العنوان: |
A Semi-Automated Solution Approach Selection Tool for Any Use Case via Scopus and OpenAI: a Case Study for AI/ML in Oncology |
| المؤلفون: |
Kılıç, Deniz Kenan, Vasegaard, Alex Elkjær, Desoeuvres, Aurélien, Nielsen, Peter |
| سنة النشر: |
2023 |
| المجموعة: |
ArXiv.org (Cornell University Library) |
| مصطلحات موضوعية: |
Computer Science - Artificial Intelligence, Computer Science - Information Retrieval, Computer Science - Machine Learning |
| الوصف: |
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. ; Comment: The paper is under review in Expert Systems with Applications, Elsevier |
| نوع الوثيقة: |
text |
| اللغة: |
unknown |
| العلاقة: |
http://arxiv.org/abs/2307.04573Test |
| الإتاحة: |
http://arxiv.org/abs/2307.04573Test |
| رقم الانضمام: |
edsbas.748F9D70 |
| قاعدة البيانات: |
BASE |
