Predictive Intelligence in Medicine [electronic resource] : 6th International Workshop, PRIME 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings / edited by Islem Rekik, Ehsan Adeli, Sang Hyun Park, Celia Cintas, Ghada Zamzmi.
Contributor(s): Rekik, Islem [editor.]
| Adeli, Ehsan [editor.] | Park, Sang Hyun [editor.] | Cintas, Celia [editor.] | Zamzmi, Ghada [editor.] | SpringerLink (Online service).
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BookSeries: Lecture Notes in Computer Science: 14277Publisher: Cham : Springer Nature Switzerland : Imprint: Springer, 2023Edition: 1st ed. 2023.Description: XIII, 294 p. 97 illus., 94 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783031460050.Subject(s): Artificial intelligence | Artificial IntelligenceAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
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Springer Nature eBookSummary: This volume LNCS 14277 constitutes the refereed proceedings of the 6th International Workshop, PRIME 2023, Held in Conjunction with MICCAI 2023, in October 2023, held in Vancouver, BC, Canada. The 24 full papers presented were carefully reviewed and selected from 27 submissions. This workshop intersects ideas from both machine learning and mathematical/statistical/physical modeling research directions in the hope to provide a deeper understanding of the foundations of predictive intelligence developed for medicine, as well as to where we currently stand and what we aspire to achieve through this field. .
This volume LNCS 14277 constitutes the refereed proceedings of the 6th International Workshop, PRIME 2023, Held in Conjunction with MICCAI 2023, in October 2023, held in Vancouver, BC, Canada. The 24 full papers presented were carefully reviewed and selected from 27 submissions. This workshop intersects ideas from both machine learning and mathematical/statistical/physical modeling research directions in the hope to provide a deeper understanding of the foundations of predictive intelligence developed for medicine, as well as to where we currently stand and what we aspire to achieve through this field. .
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