暂无分享,去创建一个
Ivan Serina | Alfonso Gerevini | Luca Putelli | Matteo Olivato | Roberto Maroldi | A. Gerevini | I. Serina | R. Maroldi | Luca Putelli | Matteo Olivato
[1] G. Grunkemeier,et al. Receiver operating characteristic curve analysis of clinical risk models. , 2001, The Annals of thoracic surgery.
[2] Andreas Holzinger,et al. Data Mining with Decision Trees: Theory and Applications , 2015, Online Inf. Rev..
[3] Leo Anthony Celi,et al. Enabling Machine Learning in Critical Care. , 2017, ICU management & practice.
[4] Ivan Serina,et al. Applying Self-interaction Attention for Extracting Drug-Drug Interactions , 2019, AI*IA.
[5] S. Hyakin,et al. Neural Networks: A Comprehensive Foundation , 1994 .
[6] Bartosz Krawczyk,et al. Learning from imbalanced data: open challenges and future directions , 2016, Progress in Artificial Intelligence.
[7] Dirk Van,et al. Ensemble Methods: Foundations and Algorithms , 2012 .
[8] Andries Petrus Engelbrecht,et al. Training feedforward neural networks with dynamic particle swarm optimisation , 2012, Swarm Intelligence.
[9] Roberto Maroldi,et al. COVID-19 outbreak in Italy: experimental chest X-ray scoring system for quantifying and monitoring disease progression , 2020, La radiologia medica.
[10] Harry Zhang,et al. The Optimality of Naive Bayes , 2004, FLAIRS.
[11] Neil D. Lawrence,et al. Dataset Shift in Machine Learning , 2009 .
[12] Ivan Serina,et al. Deep Learning for Classification of Radiology Reports with a Hierarchical Schema , 2020, KES.
[13] Johan A. K. Suykens,et al. Least Squares Support Vector Machine Classifiers , 1999, Neural Processing Letters.
[14] Gaël Varoquaux,et al. Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..
[15] Ivan Serina,et al. Automatic Classification of Radiological Reports for Clinical Care , 2017, AIME.
[16] João Gama,et al. A survey on concept drift adaptation , 2014, ACM Comput. Surv..
[17] Maya R. Gupta,et al. Bayesian Quadratic Discriminant Analysis , 2007, J. Mach. Learn. Res..
[18] Aram Galstyan,et al. Multitask learning and benchmarking with clinical time series data , 2017, Scientific Data.
[19] David A. Cieslak,et al. Evaluating Probability Estimates from Decision Trees , 2006 .
[20] Mohamed Bader-El-Den,et al. Patient length of stay and mortality prediction: A survey , 2017, Health services management research.
[21] Xian-gao Jiang,et al. Towards an Artificial Intelligence Framework for Data-Driven Prediction of Coronavirus Clinical Severity , 2020 .
[22] Mihaela van der Schaar,et al. ForecastICU: A Prognostic Decision Support System for Timely Prediction of Intensive Care Unit Admission , 2016, ICML.
[23] K. Hajian‐Tilaki,et al. Receiver Operating Characteristic (ROC) Curve Analysis for Medical Diagnostic Test Evaluation. , 2013, Caspian journal of internal medicine.
[24] Rema Padman,et al. Analyzing the Effect of Data Quality on the Accuracy of Clinical Decision Support Systems: A Computer Simulation Approach , 2006, AMIA.
[25] Ivan Serina,et al. The Impact of Self-Interaction Attention on the Extraction of Drug-Drug Interactions , 2019, CLiC-it.
[26] Pierre Geurts,et al. Extremely randomized trees , 2006, Machine Learning.
[27] Shamim Nemati,et al. Machine Learning and Decision Support in Critical Care , 2016, Proceedings of the IEEE.
[28] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[29] Karsten M. Borgwardt,et al. Early prediction of circulatory failure in the intensive care unit using machine learning , 2020, Nature Medicine.
[30] L. Mombaerts,et al. A machine learning-based model for survival prediction in patients with severe COVID-19 infection , 2020, medRxiv.
[31] Ahmed M. Alaa,et al. How artificial intelligence and machine learning can help healthcare systems respond to COVID-19 , 2020, Machine Learning.