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The work is evaluated using a breast cancer prognosis system previously developed in partnership with health care professionals.
The prognosis system will be founded on a collaboration between sensor systems, advanced reasoning methods for data fusion and signal interpretation, and modeling and simulation systems.
A science-based structural integrity prognosis system (SIPS) is being developed to provide prompt, informed predictions of the structural viability of individual aircraft based on tracking of their actual use and modeling of anticipated usage.
The results obtained were very encouraging and showed that the proposed prognosis system based on health state probability estimation has the potential to be used as an estimation tool for remnant life prediction in industrial machinery.
In the area of failure prognosis, system states are typically related to critical variables whose future evolution in time might significantly affect the health condition of the process, thus yielding into a critical failure at a particular time instant -typically referred to as the Time-of-Failure (ToF).
The prognosis system SAPS3 (Simplified Acute Physiology Score 3) aims to establish a predictive mortality rate for patients admitted to Intensive Care Units (ICU).
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A number of different periodontal prognosis systems have been previously proposed but do not consider important patient-level factors, such as smoking and diabetic control, in the calculation of the expected outcome and often use subjective measures that introduce potential inaccuracies.
(8)–(15) can be coded and embedded to develop an e-prognosis system for this machine using ICT tools and accessories such as PHP (Hypertext Pre-processor), JavaScript, Google graph, application programming interface (API), jQuery, MySQL database and canvg-JavaScript SVG parser and renderer on canvas.
Accurate health prognosis ensures system reliability and aids in estimating the remaining-useful-life (RUL) which in turn reduces repair or replacement costs.
Based on this, building a disease prognosis expert system will bring a great effect on clinical medicine.
In addition, the fewer the selected genes are, the less cost the disease prognosis expert system is.
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