Towards the Interpretability of Machine Learning Predictions for Medical Applications Targeting Personalised Therapies: A Cancer Case Survey
Antonio Jesús Banegas‐Luna(Universidad Católica de Murcia), Horacio Pérez‐Sánchez(Universidad Católica de Murcia), Patrizia Ferroni(Istituti di Ricovero e Cura a Carattere Scientifico), Adrian Iftene(Alexandru Ioan Cuza University), Noemi Scarpato(San Raffaele University of Rome), Jorge Peña‐García(Universidad Católica de Murcia), Fiorella Guadagni(Vita-Salute San Raffaele University), Andrés Bueno-Crespo(Universidad Católica de Murcia), Fabio Massimo Zanzotto(University of Rome Tor Vergata)
Cited by 72
Related Papers
MCC950 closes the active conformation of NLRP3 to an inactive state
|Nature Chemical Biology|2019|446
Neural network and deep-learning algorithms used in QSAR studies: merits and drawbacks
|Drug Discovery Today|2018|224
A Comprehensive Docking and MM/GBSA Rescoring Study of Ligand Recognition upon Binding Antithrombin
|Current Topics in Medicinal Chemistry|2017|193
High-Throughput parallel blind Virtual Screening using BINDSURF
|BMC Bioinformatics|2012|190
Managing, Analysing, and Integrating Big Data in Medical Bioinformatics: Open Problems and Future Perspectives
|BioMed Research International|2014|175