Artificial Intelligence in Medicine: 15th Conference on by John H. Holmes, Riccardo Bellazzi, Lucia Sacchi, Niels Peek

By John H. Holmes, Riccardo Bellazzi, Lucia Sacchi, Niels Peek

This e-book constitutes the refereed complaints of the fifteenth convention on synthetic Intelligence in medication, AIME 2015, held in Pavia, Italy, in June 2015. the nineteen revised complete and 24 brief papers provided have been conscientiously reviewed and chosen from ninety nine submissions. The papers are geared up within the following topical sections: technique mining and phenotyping; information mining and desktop studying; temporal facts mining; uncertainty and Bayesian networks; textual content mining; prediction in medical perform; and information illustration and guidelines.

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Additional resources for Artificial Intelligence in Medicine: 15th Conference on Artificial Intelligence in Medicine, AIME 2015, Pavia, Italy, June 17-20, 2015. Proceedings

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But not all features are closely related with the treatment process of unstable angina, and it should select significant features for the unstable angina patients to improve the accuracy of predictive monitoring. To this end, we asked our clinical collaborators to pick up 21 patient features: “Age”, “Gender”, “Creatine kinase”, “Creatinine”, “Angina pectoris”, “Hypertension”, “Troponin T measurement”, “Quantitative determination of creatine kinase”, “High-sensitivity C-reactive protein”, “Diabetes”, “Renal insufficiency”, “Cardiac insufficiency”, “Hyperlipidemia”, “History of coronary heart disease”, “Blood sugar”, “Tumor”, 32 Z.

In fact, traces from the simulator are alphanumeric as well as traces from the eye-tracker. On the contrary, those from the haptic arm are numeric. Their lengths are also all different. Finally, the eye-tracker and the haptic arm record traces continuously whereas the simulator records traces exclusively when an action is executed from the interface. 4 Generating Perceptual-Gestural Sequences In this section we describe the treatment performed for generating perceptual-gestural sequences from the heterogeneous multisource simulation traces that we presented in the previous section.

Then, the semantization operator is applied for transposing changes in the coordinates of the simulation tools into semantic states. These changes are the consequences of executed actions and gestures. g. “the fluoroscope has a caudal incline”; “the trocar is quickly inclined on the sagittal axis”). , the positions of all the tools, in each generated perceptual-gestural sequence. In its actual version, the semantization operator uses a simple mapping method that takes as input the coordinates of the simulation tools as Euclidean vectors and link the changes of these coordinates through the interaction sequences into manually recorded semantic denominations.

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