Machine learning algorithm to predict the long-term adverse cardiovascular events following coronary artery bypass surgery (CABG)
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Updated
Dec 26, 2022 - Python
Machine learning algorithm to predict the long-term adverse cardiovascular events following coronary artery bypass surgery (CABG)
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Tools to test BNN inference algorithms and techniques to predict RUL on aeronautical systems.
ML Approaches for RUL Prediction, Anomaly Detection, Survival Analysis and Failure Classification
The NASA Prognostics As-A-Service (PaaS) Sandbox is a simplified implementation of a Software Oriented Architecture (SOA) for performing prognostics (estimation of time until events and future system states) of engineering systems. The PaaS Sandbox is a wrapper around the Prognostics Algorithms Package and Prognostics Models Package, allowing on…
Evolutionary Neural Architecture Search on Transformers for RUL Prediction
The NASA Prognostic Python Packages is a Python framework focused on defining and building models and algorit for prognostics (computation of remaining useful life) of engineering systems, and provides a set of models and algorithms for select components developed within this framework, suitable for use in prognostic applications.
remaining useful life, residual useful life, remaining life estimation, survival analysis, degradation models, run-to-failure models, condition-based maintenance, CBM, predictive maintenance, PdM, prognostics health management, PHM
The Prognostic Algorithm Package is a python framework for model-based prognostics (computation of remaining useful life) of engineering systems, and provides a set of algorithms for state estimation and prediction, including uncertainty propagation. The algorithms take as inputs prognostic models (from NASA's Prognostics Model Package), and per…
Using knowledge-informed machine learning on the PRONOSTIA (FEMTO) and IMS bearing data sets. Predict remaining-useful-life (RUL).
The NASA Prognostic Model Package is a Python framework focused on defining and building models for prognostics (computation of remaining useful life) of engineering systems, and provides a set of prognostics models for select components developed within this framework, suitable for use in prognostics applications for these components.
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