AI in Context: Harnessing Domain Knowledge for Smarter Machine Learning

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 sec...

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Published inApplied sciences Vol. 14; no. 24; p. 11612
Main Authors Miller, Tymoteusz, Durlik, Irmina, Łobodzińska, Adrianna, Dorobczyński, Lech, Jasionowski, Robert
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.12.2024
Subjects
Accuracy
AI/ML ethical practices
Algorithms
Analysis
Artificial intelligence
Breast cancer
Case studies
Computational linguistics
domain expertise in AI
Ethical aspects
Ethics
Forecasts and trends
industry-specific AI applications
Innovations
Knowledge
Language processing
Machine learning
Mammography
Manufacturing industry
Medical diagnosis
Natural language interfaces
predictive analytics in AI
Robots
Simulation
Subject specialists
technological innovation in AI/ML
Trends
Poland
United States
Online AccessGet full text
ISSN2076-3417
2076-3417
DOI10.3390/app142411612

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Abstract 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.
AbstractList 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.
Audience Academic
Author Miller, Tymoteusz
Durlik, Irmina
Dorobczyński, Lech
Jasionowski, Robert
Łobodzińska, Adrianna
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  surname: Jasionowski
  fullname: Jasionowski, Robert
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SubjectTerms Accuracy
AI/ML ethical practices
Algorithms
Analysis
Artificial intelligence
Breast cancer
Case studies
Computational linguistics
domain expertise in AI
Ethical aspects
Ethics
Forecasts and trends
industry-specific AI applications
Innovations
Knowledge
Language processing
Machine learning
Mammography
Manufacturing industry
Medical diagnosis
Natural language interfaces
predictive analytics in AI
Robots
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technological innovation in AI/ML
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