AI in Context: Harnessing Domain Knowledge for Smarter Machine Learning

被引：0

作者：

Miller, Tymoteusz ^{[1
,2
]}

Durlik, Irmina ^{[3
]}

Lobodzińska, Adrianna ^{[4
]}

Dorobczyński, Lech ^{[5
]}

Jasionowski, Robert ^{[6
]}

机构：

[1] Institute of Marine and Environmental Sciences, University of Szczecin, Szczecin,71-314, Poland

[2] Faculty of Data Science and Information, INTI International University, Negeri Sembilan, Nilai,71800, Malaysia

[3] Faculty of Navigation, Maritime University of Szczecin, Szczecin,71-650, Poland

[4] Institute of Biology, University of Szczecin, Szczecin,71-316, Poland

[5] Faculty of Mechatronics and Electrical Engineering, Maritime University of Szczecin, Szczecin,71-650, Poland

[6] Faculty of Marine Engineering, Maritime University of Szczecin, Szczecin,71-650, Poland

来源：

Applied Sciences (Switzerland) | 2024年 / 14卷 / 24期

关键词：

This article delves into the critical integration of domain knowledge into AI/ML systems across various industries; highlighting its importance in developing ethically responsible; effective; and contextually relevant solutions. Through detailed case studies from the healthcare and manufacturing sectors; we explore the challenges; strategies; and successes of this integration. We discuss the evolving role of domain experts and the emerging tools and technologies that facilitate the incorporation of human expertise into AI/ML models. The article forecasts future trends; predicting a more seamless and strategic collaboration between AI/ML and domain expertise. It emphasizes the necessity of this synergy for fostering innovation; ensuring ethical practices; and aligning technological advancements with human values and real-world complexities. © 2024 by the authors;

D O I：

10.3390/app142411612

中图分类号：

学科分类号：

摘要：

引用

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