| 摘要 |
Systems for diagnostic decision support utilizing machine learning techniques are provided. A library of physiological data from prior patients can be utilized to train a classification component. Physiological data, including time parameterized data, can be mapped into finite discrete hyperdimensional space for classification. Dimensionality and resolution may be dynamically optimized. Classification mechanisms may incorporate recognition of quantitative interpretation information and exogenous effects. |
