Statistical analysis on the effectiveness of a low insulin index, alkaline and functional diet evaluated with machine learning techniques

Fabiana Antoniali; Maria Luisa Conza; Francesco Alessandro Conventi; Francesco Cirotto; Antonio D'Avanzo; Agostino De Iorio; Annalisa De Iorio; Nunzia Formicola; Manuela Forte; Federica Miele; Giovanni Perna; Biagio Rossi; Elvira Rossi

arXiv · 2409.18221

Statistical analysis on the effectiveness of a low insulin index, alkaline and functional diet evaluated with machine learning techniques

Fabiana Antoniali·Maria Luisa Conza·Francesco Alessandro Conventi·Francesco Cirotto·Antonio D'Avanzo·Agostino De Iorio·Annalisa De Iorio·Nunzia Formicola·Manuela Forte·Federica Miele·Giovanni Perna·Biagio Rossi·Elvira Rossi

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Abstract

In this paper, a statistical analysis of the performance of a low insulin index, alkaline and functional diet developed by ANTUR evaluated with machine learning techniques is reported. The sample of patients was checked on a regular basis with a BioImpedenziometric (BIA) analysis. The BIA gives about 40 parameters output describing the health status of the patient. The sample of 1626 patients was grouped in clusters with similar characteristics by a neural network algorithm. A study of the behaviour of the BIA parameters evolution over time with respect to the first visit was performed. More than the 75% of the patient that followed the ANTUR diet showed an improvement of the health status.

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Fabiana Antoniali, Maria Luisa Conza, Francesco Alessandro Conventi, Francesco Cirotto, Antonio D'Avanzo, Agostino De Iorio, Annalisa De Iorio, Nunzia Formicola, Manuela Forte, Federica Miele, Giovanni Perna, Biagio Rossi, Elvira Rossi. 2024-09-26. Statistical analysis on the effectiveness of a low insulin index, alkaline and functional diet evaluated with machine learning techniques. https://arxiv.org/abs/2409.18221

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