Artificial intelligence algorithms for prostate cancer prediction by breath analysis

Tuesday February 20th, 2024

Sorry, this entry is only available in Italian.

A. Lo Sasso, L. Bellantuono, R. Manetta, A. Gazzerro, R. Di Filippo, F. Porcelli, L. Facchini, P. Frascella and R. Bellotti

Dipartimento Interateneo di Fisica, Universita` degli Studi di Bari – Bari, Italy
Predict S.r.l. – Fiera del Levante, Bari, Italy
Istituto Nazionale di Fisica Nucleare, Sezione di Bari – Bari, Italy
Dipartimento di Biomedicina Traslazionale e Neuroscienze (DiBraiN), Universita` degli Studi di Bari – Bari, Italy
Dipartimento di Emergenza Urgenza e Accettazione, Ospedale S. Salvatore L’Aquila, Italy
Scuola di Specializzazione in Radiologia, Ospedale S. Salvatore – L’Aquila, Italy

Breath analysis is emerging as a promising screening technique. Analysis of volatile organic compounds by artificial intelligence can lead to an early warning bell by noninvasive screening. In this work, we analyze volatile organic compounds from patients who had undergone a prostate cancer exam. We expose a computational methodology to discriminate suspected and full-blown patients. We adopt a sample selection and use oversampling to train a neural network based on a Multi-Layer Perceptron in order to predict real data and simulate performances on further patients undergoing prostate cancer screening.

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Artificial intelligence algorithms for prostate cancer prediction by breath analysis

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