University of Milano-Bicocca

AI applications to medical images: From machine learning to deep learning

Isabella Castiglioni, Leonardo Rundo, Marina Codari et al.

2021 · 694 Zit.

Explainable Artificial Intelligence (XAI) 2.0: A manifesto of open challenges and interdisciplinary research directions

Luca Longo, Mario Brčić, Federico Cabitza et al.

2024 · 447 Zit.

The need to separate the wheat from the chaff in medical informatics

Federico Cabitza, Andrea Campagner

2021 · 263 Zit.

The importance of being external. methodological insights for the external validation of machine learning models in medicine

Federico Cabitza, Andrea Campagner, Felipe Soares et al.

2021 · 248 Zit.

Machine Learning in Orthopedics: A Literature Review

Federico Cabitza, Angela Locoro, Giuseppe Banfi

2018 · 244 Zit.

Experimental evidence of effective human–AI collaboration in medical decision-making

Carlo Reverberi, Tommaso Rigon, Aldo Solari et al.

2022 · 191 Zit.

Potentials and pitfalls of ChatGPT and natural-language artificial intelligence models for the understanding of laboratory medicine test results. An assessment by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Working Group on Artificial Intelligence (WG-AI)

Janne Cadamuro, Federico Cabitza, Željko Debeljak et al.

2023 · 114 Zit.

Bridging the “last mile” gap between AI implementation and operation: “data awareness” that matters

Federico Cabitza, Andrea Campagner, Clara Balsano

2020 · 109 Zit.

Rising adoption of artificial intelligence in scientific publishing: evaluating the role, risks, and ethical implications in paper drafting and review process

Anna Carobene, Andrea Padoan, Federico Cabitza et al.

2023 · 104 Zit.

A framework for validating AI in precision medicine: considerations from the European ITFoC consortium

Rosy Tsopra, Xosé M. Fernández, Claudio Luchinat et al.

2021 · 100 Zit.

Machine learning in laboratory medicine: waiting for the flood?

Federico Cabitza, Giuseppe Banfi

2017 · 97 Zit.

Rams, hounds and white boxes: Investigating human–AI collaboration protocols in medical diagnosis

Federico Cabitza, Andrea Campagner, Luca Ronzio et al.

2023 · 92 Zit.

Machine learning applied on chest x-ray can aid in the diagnosis of COVID-19: a first experience from Lombardy, Italy

Isabella Castiglioni, Davide Ippolito, Matteo Interlenghi et al.

2021 · 86 Zit.

Artificial intelligence applied on chest X-ray can aid in the diagnosis of COVID-19 infection: a first experience from Lombardy, Italy

Isabella Castiglioni, Davide Ippolito, Matteo Interlenghi et al.

2020 · 85 Zit.

Clinical Trial Design Principles and Outcomes Definitions for Device-Based Therapies for Hypertension: A Consensus Document From the Hypertension Academic Research Consortium

David E. Kandzari, Felix Mahfoud, Michael A. Weber et al.

2022 · 72 Zit.