BACKGROUND AND SCOPE
Clinical trial design in oncology relies heavily on evidence synthesized from prior studies. However, relevant information, including Kaplan-Meier curves, baseline characteristics, and eligibility criteria, is typically embedded in figures, tables, and free text, making systematic extraction and qu...
Guan-Nan Gong, Satrajit Roychoudhury, A. Meisner et al.· JCO Clinical Cancer Informat...· 0 citations
Background Breast cancer (BC) mortality risk extends over decades; yet, the temporal prognostic patterns of histological grade across subtypes and stages remain unclear. Patients and methods Women with stage I-III BC diagnosed between 2000 and 2018 were identified from Surveillance, Epidemiology, and End Results regist...
M. Mariani, M. Ochocki, G. Bianchini et al.· ESMO Open· 0 citations
A workflow to minimize the effect of WES capture inconsistencies in single-nucleotide variation (SNV) data is proposed, which leads to a considerable decrease in the batch effect signal, potentially increasing the likelihood of finding true biological signals.
Laura Jarosz, M. Ochocki, Julia Merta et al.· Methods and Protocols· 0 citations
FastBindRank is presented, a distillation-based framework that transfers the predictive power of a high-accuracy structure-based model (Boltz-2) into a computationally efficient sequence-based surrogate and can identify functionally active novel compounds from ultra-large virtual screening.
J. Dai, Yueyue Wang, N. Shan et al.· Clinical Cancer Research· 0 citations
Distillation is established as a practical strategy for scalable, high-fidelity virtual screening of ultra-large chemical libraries by transferring the predictive power of the structure-based model Boltz-2 into an efficient sequence-based surrogate, FastBindRank.
J. Dai, Yueyue Wang, N. Shan et al.· bioRxiv· 0 citations
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