Fondazione Italiana Linfomi
Commissione Studi Biologici e Bioinformatici
AI-CSBB is an initiative of the CSBB Commission aimed at building a collaborative research community capable of harnessing the power of artificial intelligence to extract crucial insights for understanding lymphoma — from disease onset to therapeutic response.
According to this, the FIL-CSBB created a repository encompassing recognized publicly available datasets to benchmark the development of analytical and artificial intelligence (AI) methods as a clinical hypothesis generator. A total of 11 studies (published from 2017 onward) were included, encompassing a total of 15 cohorts (A) C. Sha, Journal of Clinical Oncology, 2018 (B) K. Wenzl, Blood Cancer Journal, 2024 (C) F. Cucco, Leukemia, 2019 (D) B. Chapuy, Nature Medicine, 2018 (E) L. Pedrosa, Scientific Reports, 2021 (F) S. E. Lacy, Targeted sequencing in DLBCL, 2020 (G) G. Wright, Cancer Cell, 2020 (H) D. Ennishi, Journal of Clinical Oncology, 2018 (I) A. Reddy, Journal of Clinical Oncology, 2018 (J) M. Zhang, Cancer Cell, 2023. (K) R. Shen, Signal Transduction and Targeted Therapy, 2023
A first example has been implemented on Diffuse Large B-Cell Lymphoma (DLBCL). According to this, the AI-CSBB created a repository encompassing recognized publicly available datasets to benchmark the development of analytical and AI methods as a clinical hypothesis generator.