Usefulness of DXA-based bone strain index in postmenopausal women with type 2 diabetes mellitus.

Unlabelled: Bone Strain Index (BSI) is a new dual-energy x-ray absorptiometry (DXA)-based index. We retrospectively evaluated data from 153 postmenopausal women with a history of type 2 diabetes mellitus (T2DM). Lumbar spine and femoral Bone Strain Index (BSI) were sensitive to skeletal impairment in postmenopausal women suffering from T2DM.

Towards an objective theory of subjective liking: A first step in understanding the sense of beauty.

The study of the electroencephalogram signals recorded from subjects during an experience is a way to understand the brain processes that underlie their physical and emotional involvement. Such signals have the form of time series, and their analysis could benefit from applying techniques that are specific to this kind of data. Neuroaesthetics, as defined by Zeki in 1999, is the scientific approach to the study of aesthetic perceptions of art, music, or any other experience that can give rise to aesthetic judgments, such as liking or disliking a painting.

The voice of COVID-19: Breath and cough recording classification with temporal decision trees and random forests.

Symbolic learning is the logic-based approach to machine learning, and its mission is to provide algorithms and methodologies to extract logical information from data and express it in an interpretable way. Interval temporal logic has been recently proposed as a suitable tool for symbolic learning, specifically via the design of an interval temporal logic decision tree extraction algorithm. In order to improve their performances, interval temporal decision trees can be embedded into interval temporal random forests, mimicking the corresponding schema at the propositional level.

An intelligent clustering method for devising the geochemical fingerprint of underground aquifers.

Geochemical fingerprinting is a rapidly expanding discipline in the earth and environmental sciences, anchored in the recognition that geological processes leave behind physical, chemical and sometimes also isotopic patterns in the samples. Furthermore, the geochemical fingerprinting of natural cycles (water, carbon, soil and biota fingerprinting) are influenced by the anthropogenic impact and by the climate change. So, their monitoring is a tool of resilience and adaptation.

Predicting treatment recommendations in postmenopausal osteoporosis.

We designed, implemented, and tested a clinical decision support system at the Research Center for the Study of Menopause and Osteoporosis within the University of Ferrara (Italy). As an independent module of our system, we implemented an original machine learning system for rule extraction, enriched with a hierarchical extraction methodology and a novel rule evaluation technique. Such a module is used in everyday operation protocol, and it allows physicians to receive suggestions for prevention and treatment of osteoporosis.