Introducing Serendipity in a Content-Based Recommender System. - Leo Iaquinta; Marco de Gemmis; Pasquale Lops; Giovanni Semeraro; Michele Filannino; Piero Molino (HIS, 2008)

DBWorld e-mails. - Michele Filannino (UCI Machine Learning Repository, 2011)

Temporal expression normalisation in natural language texts - Michele Filannino (CoRR, 2012)

ManTIME: Temporal expression identification and normalization in the TempEval-3 challenge. - Michele Filannino; Gavin Brown 001; Goran Nenadic (SemEval@NAACL-HLT, 2013)

Combining rules and machine learning for extraction of temporal expressions and events from clinical narratives. - Aleksandar Kovacevic; Azad Dehghan; Michele Filannino; John A. Keane; Goran Nenadic (J. Am. Medical Informatics Assoc., 2013)

Using Machine Learning to Predict Temporal Orientation of Search Engines' Queries in the Temporalia Challenge. - Michele Filannino; Goran Nenadic (NTCIR, 2014)

Temporal expression extraction with extensive feature type selection and a posteriori label adjustment. - Michele Filannino; Goran Nenadic (Data Knowl. Eng., 2015)

Data-driven temporal information extraction with applications in general and clinical domains. - Michele Filannino (2016)

Extracting and Normalizing Adverse Drug Reactions from Drug Labels. - Carson Tao; Kahyun Lee; Michele Filannino; Kevin Buchan; Kathy Lee; Tilak Raj Arora; Joey Liu; Oladimeji Farri; Özlem Uzuner (TAC, 2017)

A Hybrid Approach to Precision Medicine-related Biomedical Article Retrieval and Clinical Trial Matching. - Yuan Ling; Sadid A. Hasan; Michele Filannino; Kevin P. Buchan; Kahyun Lee; Joey Liu; William Boag; Di Jin; Özlem Uzuner; Kathy Lee; Vivek V. Datla; Ashequl Qadir; et al. (TREC, 2017)

Automatic prediction of coronary artery disease from clinical narratives. - Kevin Buchan; Michele Filannino; Özlem Uzuner (J. Biomed. Informatics, 2017)

Prescription extraction using CRFs and word embeddings. - Carson Tao; Michele Filannino; Özlem Uzuner (J. Biomed. Informatics, 2017)

Precision Medicine: matching cancer patients with clinical trials. - Michele Filannino; Kahyun Lee; Di Jin; Kevin Buchan; William Boag; Özlem Uzuner (AMIA, 2018)

Precision Medicine: matching cancer patients with relevant treatments. - Kahyun Lee; Michele Filannino; Di Jin; Kevin Buchan; William Boag; Özlem Uzuner (AMIA, 2018)

FABLE: A Semi-Supervised Prescription Information Extraction System. - Carson Tao; Michele Filannino; Özlem Uzuner (AMIA, 2018)

Extracting ADRs from Drug Labels using Bi-LSTM and CRFs. - Carson Tao; Michele Filannino; Özlem Uzuner (AMIA, 2018)

Corrigendum to "Symptom severity prediction from neuropsychiatric clinical records: Overview of 2016 CEGS N-GRID shared tasks Track 2" [J Biomed Inform. 2017 Nov;75S: S62-S70]. - Michele Filannino; Amber Stubbs; Özlem Uzuner (J. Biomed. Informatics, 2018)

An Empirical Test of GRUs and Deep Contextualized Word Representations on De-Identification. - Kahyun Lee; Michele Filannino; Özlem Uzuner (MedInfo, 2019)

An Exploratory Study on Pseudo-Data Generation in Prescription and Adverse Drug Reaction Extraction. - Carson Tao; Kahyun Lee; Michele Filannino; Özlem Uzuner (MedInfo, 2019)

Cohort selection for clinical trials: n2c2 2018 shared task track 1. - Amber Stubbs; Michele Filannino; Ergin Soysal; Samuel Henry 001; Özlem Uzuner (J. Am. Medical Informatics Assoc., 2019)

2018 n2c2 shared task on adverse drug events and medication extraction in electronic health records. - Sam Henry 001; Kevin Buchan; Michele Filannino; Amber Stubbs; Özlem Uzuner (J. Am. Medical Informatics Assoc., 2020)

Towards Productizing AI/ML Models: An Industry Perspective from Data Scientists. - Filippo Lanubile; Fabio Calefato; Luigi Quaranta; Maddalena Amoruso; Fabio Fumarola; Michele Filannino (WAIN@ICSE, 2021)

Blaze-IT: A Lightweight BERT Model for the Italian Language. - Francesco Russo; Michele Filannino (CLiC-it, 2023)

GitHub Copilot: a systematic study. - Alessandro Benetti; Michele Filannino (Ital-IA, 2024)