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Pantano F, Manca P, Armento G, et al. Breakthrough Cancer Pain Clinical Features and Differential Opioids Response: A Machine Learning Approach in Patients With Cancer From the IOPS-MS Study. JCO Precis Oncol. 2020;4doi: 10.1200/PO.20.00158.
Pantano, F., Manca, P., Armento, G., Zeppola, T., Onorato, A., Iuliani, M., Simonetti, S., Vincenzi, B., Santini, D., Mercadante, S., Marchetti, P., Cuomo, A., Caraceni, A., Mediati, R. D., Vellucci, R., Mammucari, M., Natoli, S., Lazzari, M., Dauri, M., Adile, C., Airoldi, M., Azzarello, G., Blasi, L., Chiurazzi, B., Degiovanni, D., Fusco, F., Guardamagna, V., Liguori, S., Palermo, L., Mameli, S., Masedu, F., Mazzei, T., Melotti, R. M., Menardo, V., Miotti, D., Moroso, S., Pascoletti, G., De Santis, S., Orsetti, R., Papa, A., Ricci, S., Scelzi, E., Sofia, M., Aielli, F., Valle, A., & Tonini, G. (2020). Breakthrough Cancer Pain Clinical Features and Differential Opioids Response: A Machine Learning Approach in Patients With Cancer From the IOPS-MS Study. JCO precision oncology, 4. https://doi.org/10.1200/PO.20.00158
Pantano, Francesco, et al. "Breakthrough Cancer Pain Clinical Features and Differential Opioids Response: A Machine Learning Approach in Patients With Cancer From the IOPS-MS Study." JCO precision oncology vol. 4 (2020). doi: https://doi.org/10.1200/PO.20.00158
Pantano F, Manca P, Armento G, Zeppola T, Onorato A, Iuliani M, Simonetti S, Vincenzi B, Santini D, Mercadante S, Marchetti P, Cuomo A, Caraceni A, Mediati RD, Vellucci R, Mammucari M, Natoli S, Lazzari M, Dauri M, Adile C, Airoldi M, Azzarello G, Blasi L, Chiurazzi B, Degiovanni D, Fusco F, Guardamagna V, Liguori S, Palermo L, Mameli S, Masedu F, Mazzei T, Melotti RM, Menardo V, Miotti D, Moroso S, Pascoletti G, De Santis S, Orsetti R, Papa A, Ricci S, Scelzi E, Sofia M, Aielli F, Valle A, Tonini G. Breakthrough Cancer Pain Clinical Features and Differential Opioids Response: A Machine Learning Approach in Patients With Cancer From the IOPS-MS Study. JCO Precis Oncol. 2020 Nov 04;4. doi: 10.1200/PO.20.00158. eCollection 2020. PMID: 33283139; PMCID: PMC7713587.
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