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| Main Authors: | , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2409.18221 |
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| _version_ | 1866916412345286656 |
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| author | Antoniali, Fabiana Conza, Maria Luisa Conventi, Francesco Alessandro Cirotto, Francesco D'Avanzo, Antonio De Iorio, Agostino De Iorio, Annalisa Formicola, Nunzia Forte, Manuela Miele, Federica Perna, Giovanni Rossi, Biagio Rossi, Elvira |
| author_facet | Antoniali, Fabiana Conza, Maria Luisa Conventi, Francesco Alessandro Cirotto, Francesco D'Avanzo, Antonio De Iorio, Agostino De Iorio, Annalisa Formicola, Nunzia Forte, Manuela Miele, Federica Perna, Giovanni Rossi, Biagio Rossi, Elvira |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_18221 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Statistical analysis on the effectiveness of a low insulin index, alkaline and functional diet evaluated with machine learning techniques Antoniali, Fabiana Conza, Maria Luisa Conventi, Francesco Alessandro Cirotto, Francesco D'Avanzo, Antonio De Iorio, Agostino De Iorio, Annalisa Formicola, Nunzia Forte, Manuela Miele, Federica Perna, Giovanni Rossi, Biagio Rossi, Elvira Quantitative Methods Applied Physics Data Analysis, Statistics and Probability 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. |
| title | Statistical analysis on the effectiveness of a low insulin index, alkaline and functional diet evaluated with machine learning techniques |
| topic | Quantitative Methods Applied Physics Data Analysis, Statistics and Probability |
| url | https://arxiv.org/abs/2409.18221 |