Artificial Intelligence-based Planning
Artificial Intelligence-Based Planning is a computational decision-making framework within digital treatment planning that employs artificial intelligence algorithms to autonomously generate, optimize, or adapt clinical treatment strategies through data-driven learning and pattern recognition distinct from rule-based or manual planning approaches.
141
Publications
6.1K
Citations
559
Authors
266
Institutions
Publications per year
2017–2026
71
Parents
141
A New Direction in AI: Toward a Computational Theory of Perceptions
Lotfi A. Zadeh · AI Magazine · 2001 · 381 citations
Computational planning of the synthesis of complex natural products
Barbara Mikulak-Klucznik, Patrycja Gołębiowska, Alison A. Bayly et al. · Nature · 2020 · 276 citations · Full text
FF: The Fast-Forward Planning System
Jöerg Hoffmann · 2001 · 245 citations
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266
Stanford University
Stanford, United States
3 h-index
7 publications
298 citations

University of Toronto
Toronto, Canada
3 h-index
9 publications
562 citations
The University of Texas Southwestern Medical Center
Dallas, United States
3 h-index
17 publications
381 citations
Duke Medical Center
Durham, United States
3 h-index
12 publications
579 citations
KU Leuven
Leuven, Belgium
3 h-index
7 publications
513 citations

University of Notre Dame
Notre Dame, United States
3 h-index
5 publications
117 citations
University of Wisconsin–Madison
Madison, United States
2 h-index
3 publications
57 citations
Tsinghua–Berkeley Shenzhen Institute
Shenzhen, China
2 h-index
3 publications
107 citations
1–8 of 266
5 publications · 602 citations
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3 publications · 309 citations
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2 publications · 61 citations
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JETAI · 2 publications · 39 citations
2
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Repository · 2 publications · 82 citations
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