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Your search keyword '"Chiovati, Paola"' showing total 11 results
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11 results on '"Chiovati, Paola"'

2. Clinical Use of a Commercial Artificial Intelligence-Based Software for Autocontouring in Radiation Therapy: Geometric Performance and Dosimetric Impact

Author

Hoque, S M Hasibul, primary, Pirrone, Giovanni, additional, Matrone, Fabio, additional, Donofrio, Alessandra, additional, Fanetti, Giuseppe, additional, Caroli, Angela, additional, Rista, Rahnuma Shahrin, additional, Bortolus, Roberto, additional, Avanzo, Michele, additional, Drigo, Annalisa, additional, and Chiovati, Paola, additional

Published
2023
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6. Artificial Intelligence-Based Patient Selection for Deep Inspiration Breath-Hold Breast Radiotherapy from Respiratory Signals.

Author

Vendrame, Alessandra, Cappelletto, Cristina, Chiovati, Paola, Vinante, Lorenzo, Parvej, Masud, Caroli, Angela, Pirrone, Giovanni, Barresi, Loredana, Drigo, Annalisa, and Avanzo, Michele

Subjects
ARTIFICIAL intelligence, PATIENT selection, SIMULATED patients, BREAST, RECURRENT neural networks, COMPUTED tomography
Abstract

Purpose: to predict eligibility for deep inspiration breath-hold (DIBH) radiotherapy (RT) treatment of patients with left breast cancer from analysis of respiratory signal, using Deep Bidirectional Long Short-Term Memory (BLSTM) recurrent neural networks. Methods: The respiratory traces from 36 patients who underwent DIBH RT were collected. The patients' RT treatment plans were generated for both DIBH and free-breathing (FB) modalities. The patients were divided into two classes (patient eligible or not), based on the decrease of maximum dose to the left anterior descending (LAD) artery achieved with DIBH, compared to that achieved with FB and ΔDL. Patients with ΔDL > median value of ΔDL within the patient cohort were assumed to be those selected for DIBH. A BLSTM-RNN was trained for classification of patients eligible for DIBH by analysis of their respiratory signals, as acquired during acquisition of the pre-treatment computed tomography (CT), for selecting the window for DIBH. The dataset was split into training (60%) and test groups (40%), and the hyper-parameters, including the number of hidden layers, the optimizer, the learning rate, and the number of epochs, were selected for optimising model performance. The BLSTM included 2 layers of 100 neural units, each followed by a dropout layer with 20% dropout, and was trained in 35 epochs using the Adam optimizer, with an initial learning rate of 0.0003. Results: The system achieved accuracy, specificity, and sensitivity of, F1 score and area under the receiving operating characteristic curve (AUC) of 71.4%, 66.7%, 80.1%, 72.4%, and 69.4% in the test dataset, respectively. Conclusions: The proposed BLSTM-RNN classified patients in the test set eligible for DIBH with good accuracy. These results look promising for building an accurate and robust decision system to provide automated assistance to the radiotherapy team in assigning patients to DIBH. [ABSTRACT FROM AUTHOR]

Published
2023
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8. Prognostic Nutritional Index Predicts Toxicity in Head and Neck Cancer Patients Treated with Definitive Radiotherapy in Association with Chemotherapy

Author

Fanetti, Giuseppe, primary, Polesel, Jerry, additional, Fratta, Elisabetta, additional, Muraro, Elena, additional, Lupato, Valentina, additional, Alfieri, Salvatore, additional, Gobitti, Carlo, additional, Minatel, Emilio, additional, Matrone, Fabio, additional, Caroli, Angela, additional, Revelant, Alberto, additional, Lionello, Marco, additional, Zammattio Polentin, Viviana, additional, Ferretti, Andrea, additional, Guerrieri, Roberto, additional, Chiovati, Paola, additional, Bertolin, Andy, additional, Giacomarra, Vittorio, additional, Paoli, Antonino De, additional, Vaccher, Emanuela, additional, Sartor, Giovanna, additional, Steffan, Agostino, additional, and Franchin, Giovanni, additional

Published
2021
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9. Partial prostate re-irradiation for the treatment of isolated local recurrence of prostate cancer in patients previously treated with primary external beam radiotherapy: short-term results of a monocentric study

Author

Matrone, Fabio, primary, Revelant, Alberto, additional, Fanetti, Giuseppe, additional, Polesel, Jerry, additional, Chiovati, Paola, additional, Avanzo, Michele, additional, Renzi, Filippo De, additional, Colombo, Carlotta Benedetta, additional, Arcicasa, Mauro, additional, De Paoli, Antonino, additional, Franchin, Giovanni, additional, and Bortolus, Roberto, additional

Published
2021
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