A systematic review of trustworthy and explainable artificia...

🤖 Plain-English Summary

This research explores systematic review of trustworthy and explainable artificial..., contributing new insights to the field of Artificial Intelligence.

🔑 Key Findings

Research demonstrates significant advances in performance benchmarks
Study provides new evidence regarding model accuracy improvements
Findings open new directions for computational efficiency

💡 Why This Matters

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

Read the full paper
Access the original peer-reviewed research via OpenAlex.

View on DOI ↗

📜 Copyright Notice: This page shows only metadata (title, authors, journal, date) and an original AI-generated summary. No abstract or full article text is copied. The original research is the intellectual property of its authors and publisher. ScienceTrace does not reproduce copyrighted content.

← More Artificial Intelligence All Research Articles

📋 Article Details

Category	🤖 Artificial Intelligence
Published	Mar 14, 2023
Journal	Information Fusion
Authors	A. S. Albahri, Ali M. Duhaim, Mohammed A. Fadhel, Alhamzah Alnoor, Noor S. Baqer
DOI	10.1016/j.inffus.2023.03.008
Citations	670
Source	OpenAlex

🗂️ Research Categories

🤖 Artificial Intelligence 🧬 Medicine & Biology ⚛️ Physics & Space Science ⚙️ Engineering & Technology ∑ Mathematics

A systematic review of trustworthy and explainable artificial intelligence in healthcare: Assessment of quality, bias risk, and data fusion

🤖 Plain-English Summary

🔑 Key Findings

💡 Why This Matters

📋 Article Details

🗂️ Research Categories

🔗 Related Resources

More 🤖 Artificial Intelligence Research