Naciri, L.C.; Mastinu, M.; Melis, M.; Green, T.; Wolf, A.; Hummel, T.; Tomassini Barbarossa, I. A Supervised Learning Regression Method for the Analysis of the Taste Functions of Healthy Controls and Patients with Chemosensory Loss. Biomedicines2023, 11, 2133.
Naciri, L.C.; Mastinu, M.; Melis, M.; Green, T.; Wolf, A.; Hummel, T.; Tomassini Barbarossa, I. A Supervised Learning Regression Method for the Analysis of the Taste Functions of Healthy Controls and Patients with Chemosensory Loss. Biomedicines 2023, 11, 2133.
Naciri, L.C.; Mastinu, M.; Melis, M.; Green, T.; Wolf, A.; Hummel, T.; Tomassini Barbarossa, I. A Supervised Learning Regression Method for the Analysis of the Taste Functions of Healthy Controls and Patients with Chemosensory Loss. Biomedicines2023, 11, 2133.
Naciri, L.C.; Mastinu, M.; Melis, M.; Green, T.; Wolf, A.; Hummel, T.; Tomassini Barbarossa, I. A Supervised Learning Regression Method for the Analysis of the Taste Functions of Healthy Controls and Patients with Chemosensory Loss. Biomedicines 2023, 11, 2133.
Abstract
In healthy humans, taste sensitivity varies widely, influencing food selection and nutritional status. Chemosensory reductions have been associated with numerous pathological disorders or pharmacological interventions. Reliable psychophysical methods are crucial resources to analyze the taste function during routine clinical assessment. However, in the daily clinical routine, they are often considered to be too time-consuming. We used the Supervised Learning (SL) regression method to analyze with high precision the overall taste status of healthy controls (HC) and patients with chemosensory loss and to characterize the combination of responses that best can predict the overall taste status of two groups. Random Forest regressor allowed us to achieve our objective. The analysis of the order of importance and impact of each parameter on the prediction of overall taste status in the two groups showed that salty (low concentration) and sour (high concentration) stimuli specifically characterized healthy subjects, while bitter (high concentration) and astringent (high concentration) stimuli identified patients with chemosensory loss. The identification of these distinctions appears to be of interest to the health system since they may allow the use of specific stimuli during routine clinical assessments of taste function reducing the commitment in terms of time and costs.
Keywords
general taste status; taste loss; supervised learning regression; random forest regressor
Subject
Medicine and Pharmacology, Neuroscience and Neurology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
,
,
,
*
,
*
