Genetic-fuzzy optimization algorithm for adaptive learning of human vocalization in robotics

We present a computational model of human vocalization which aims at learning the articulatory mechanisms which produce spoken phonemes. It uses a set of fuzzy rules and genetic optimization. The former represents the relationships between places of articulations and speech acoustic parameters, while the latter computes the degrees of membership of the places of articulation. That is, the places of articulation are considered as fuzzy sets whose degrees of membership are the articulatory features. Subjective listening tests of sentences artificially generated from the articulatory description resulted in an average phonetic accuracy of about 76 %. Through the analysis of a large amount of natural speech, the algorithm can be used to learn the places of articulation of all phonemes

Pre-procedural ATI score (age-thrombus burden-index of microcirculatory resistance) predicts long-term clinical outcomes in patients with ST elevation myocardial infarction treated with primary percutaneous coronary intervention

Background: The ATI (Age-Thrombus burden-Index of Microvascular Resistance [IMR]) score was developed to predict suboptimal myocardial reperfusion in patients with ST-Elevation Myocardial Infarction (STEMI). When applied in the early phases of revascularization (e.g. before stent insertion), it predicts which patients are most likely to have a larger infarct size. In this study, we assessed the score's utility in determining which STEMI patients are at highest risk of clinical events during follow-up. Methods: The ATI-score was calculated prospectively in 254 STEMI patients using age (>50 years = 1 point), pre-stenting IMR (>40 U and < 100 U = 1 point; 65100 U = 2 points) and angiographic thrombus score (4 = 1 point, 5 = 3 points); the cohort was stratified in high vs. low-intermediate ATI-score strata ( 654 vs. < 4, respectively). Results: After 3 years of follow-up, patients with high ATI-score presented a higher rate of Major Adverse Cardiac Events (MACE) defined as the composite of all-cause mortality, resuscitated cardiac arrest and new heart failure diagnosis (Hazard Ratio [HR]: 3.07; 95% Confidence Interval [CI]: 1.19\u20137.93; p = 0.02). The ATI-score showed a moderate discriminative power (c-stat: 0.69), not significantly different from that of other risk scores used in the STEMI setting. A high ATI-score was an independent predictor of MACE (HR: 3.24; 95% CI: 1.22\u20138.58; p = 0.018). Conclusions: The ATI-score can discriminate patients at higher risk of long-term adverse events. The score allows predication of subsequent events even before coronary stenting, and consequently it may allow the option of individualized therapy in the early stages of the clinical care-pathway