. 2022 Jul 19;14(14):3498. doi: 10.3390/cancers14143498

Table 5.

Overview of the main topics for future clinical AI research in PDAC imaging.

Research Agenda for Clinical AI in PDAC Imaging
- To acquire more, good quality data coming from large, well-curated, multi-institutional private and public PDAC datasets - To switch focus towards state-of-the-art, entirely data-driven deep learning models - To use better quality ground truths that represent actual clinical endpoints such as overall survival and disease-free survival as the gold standard for model development - To investigate the use of multimodal AI, combining information from imaging, histopathology, genetics and clinical records

Research Agenda for Clinical AI in PDAC Imaging

-
To acquire more, good quality data coming from large, well-curated, multi-institutional private and public PDAC datasets
-
To switch focus towards state-of-the-art, entirely data-driven deep learning models
-
To use better quality ground truths that represent actual clinical endpoints such as overall survival and disease-free survival as the gold standard for model development
-
To investigate the use of multimodal AI, combining information from imaging, histopathology, genetics and clinical records