Abstract
Asier Rabasco Meneghetti
Abstract
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Confidence 100%
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Confidence 99%
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Classification of surgical complications: a new proposal with evaluation in a cohort of 6336 patients and results of a survey
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The target trial framework for causal inference from observational data: why and when is it helpful?
10.7326/annals-24-01871 · doi-reference
Using big data to emulate a target trial when a randomized trial is not available
10.1093/aje/kwv254 · doi-reference
Foundation models in radiology: what, how, why, and why not
10.1148/radiol.240597 · doi-reference
Radiomics in gastric cancer: advancing precision medicine
10.5230/jgc.2026.26.e24 · doi-reference
A multimodal deep learning model for preoperative prediction of post-operative complications in gastric cancer
10.1016/j.annonc.2026.07.004 · doi-reference
A nomogram for predicting postoperative complications based on tumor spectral CT parameters and visceral fat area in gastric cancer patients
10.1016/j.ejrad.2023.111072 · doi-reference
Risk factors associated with complication following gastrectomy for gastric cancer: retrospective analysis of prospectively collected data based on the Clavien–Dindo system
10.1007/s11605-014-2525-1 · doi-reference
Impact of postoperative complications on gastric cancer survival
10.1016/j.surg.2024.09.031 · doi-reference
Classification of surgical complications: a new proposal with evaluation in a cohort of 6336 patients and results of a survey
10.1097/01.sla.0000133083.54934.ae · doi-reference