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Deep Learning Artificial Intelligence and Restriction Spectrum Imaging for Patient-level Detection of Clinically Significant Prostate Cancer on Biparametric Magnetic Resonance Imaging
0
Zitationen
31
Autoren
2026
Jahr
Abstract
We looked at whether adding advanced scan data (ASD) and artificial intelligence (AI) models to radiologist assessments of MRI (magnetic resonance imaging) scans was better in detecting aggressive prostate cancer (PCa). We found that adding AI models or ASD to standard scan scores improved cancer detection in comparison to standard scores alone. The results suggest that combining radiologist expertise with AI and ASD may help in earlier identification of more patients with csPCa.
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Autoren
- Yuze Song
- Mariluz Rojo Domingo
- Christopher C. Conlin
- Deondre D. Do
- Madison T. Baxter
- Anna Dornisch
- George Xu
- Aditya Bagrodia
- Tristan Barrett
- Mukesh Harisinghani
- Gary Hollenberg
- Sophia C. Kamran
- Christopher J. Kane
- Dimitri A. Kessler
- Joshua Kuperman
- Kanglung Lee
- Michael A. Liss
- Daniel J. A. Margolis
- P. Murphy
- Nabih Nakrour
- Truong Ngyuen
- Thomas L. Osinski
- Rebecca Rakow-Penner
- Shoumik Roychowdhury
- Ahmed S Shabik
- Shaun Trecarten
- Natasha Wehrli
- Eric Weinberg
- Sean A. Woolen
- Anders M. Dale
- Tyler M Seibert
Institutionen
- University of California San Diego(US)
- La Jolla Bioengineering Institute(US)
- University of Cambridge(GB)
- Massachusetts General Hospital(US)
- University of Rochester Medical Center(US)
- Artificial Intelligence Research Institute(ES)
- Artificial Intelligence in Medicine (Canada)(CA)
- Universitat de Barcelona(ES)
- Cornell University(US)
- University of California, Berkeley(US)
- The University of Texas Health Science Center at San Antonio(US)
- University of California, San Francisco(US)