Decision Support
❯
Diagnose
❯Knowledge representation - Bayesian Network
Large Companies
Knowledge representation - Bayesian Network
For:
Process Engineers.
Scope:
Applying Bayesian Networks to root cause analysis of industrial processes.
Goal:
Improve Operation Efficiency
Large Companies
Operations - Intelligent Monitoring of Infrastructures
For:
Plant Operators
Scope:
Optimization of thermal efficiency of a power plant using Machine Learning.
Goal:
Improve Operation Efficiency, Improved Employee Efficiency, Reduce costs
General Public
Healthcare - Improve Investigatory Work
For:
Radiologists
Scope:
Using machine learning to predict lung cancer from CT scans.
Goal:
Anticipate Risks
Prediction of Multidrug-Resistant TB from CT Pulmonary Images Based on Deep Learning Techniques
For:
Clinicians and medical professionals predicting multidrug-resistant (MDR) patients from drug-sensitive (DS) ones based on CT lung images.
Goal:
Improved Employee Efficiency
Large Companies
Knowledge representation - Bayesian Network
For:
Process Engineers.Goal:
Improve Operation EfficiencyProblem addressed
Root cause analysis (RCA) and decision support is vital for industrial plant maintenance. Process Engineers are face with the challenging to task of assessing issues with ever increasingly complex industrial process under high workload and stress.
Diagnostic tools are needed to provide Process Engineers with decision support for determining the origin of a process distrubance or fault. Such tools must be transparent in their reasoning and provide an easily interpretable diagnosis in order to be optimally useful.
Scope of use case
Applying Bayesian Networks to root cause analysis of industrial processes.
Sensor Network - IOT
AI: Perceive
Bayesian network
AI: Understand
Diagnose
AI: Act