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AlforCOVID: Predicting the clinical outcomes in patients with COVID-19 applying AI to chest-X-rays. An Italian multicentre study.

2021 · 91 Zit. · Florence Research (University of Florence)

How do patients perceive the AI-radiologists interaction? Results of a survey on 2119 responders

2023 · 24 Zit. · European Journal of Radiology

Artificial Intelligence Applied to Chest X-ray for Differential Diagnosis of COVID-19 Pneumonia

2021 · 22 Zit. · Diagnostics

Adoption of AI in Oncological Imaging: Ethical, Regulatory, and Medical-Legal Challenges

2023 · 5 Zit. · Critical Reviews™ in Oncogenesis

Voice to the Patients: What do they really think about the use of AI by radiologists? A Focus Group study

2023 · 3 Zit.

Structured Transformation of Unstructured Prostate MRI Reports Using Large Language Models

2025 · 2 Zit. · Tomography

Capturing patient voices: A focus group-based study unveiling the potential of AI in medical diagnosis

2024 · 1 Zit. · Human Technology

AI-based staging, causal hypothesis and progression of subjects at risk of Alzheimer’s disease: a multicenter study

2025 · 1 Zit. · Frontiers in Neurology

How patients perceive the AI-radiologists interaction? Results of a survey on 2119 responders.

2022 · 0 Zit.

Machine Learning to Predict In-Hospital Mortality in COVID-19 Patients Using Computed Tomography-Derived Pulmonary and Vascular Features

2022 · 0 Zit. · Zenodo (CERN European Organization for Nuclear Research)

How do radiologists perceive their interaction with AI? Results of a survey on 114 respondents

2023 · 0 Zit.

Machine Learning to Predict In-Hospital Mortality in COVID-19 Patients Using Computed Tomography-Derived Pulmonary and Vascular Features

2022 · 0 Zit. · Zenodo (CERN European Organization for Nuclear Research)