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Introduction Core Technology Building and Deploying Neural Networks April 2005 Using Neural Networks in Decision Support Systems Medical Procedure Certification Crime Forecasting Jack Copper NeuralWare [email protected] Hiroshi Maruyama Grain Quality Assessment SET Software Co. Ltd. [email protected] © 2005 NeuralWare. All rights reserved. P-1 NeuralWare Since 1987, NeuralWare has created and marketed neural network based Artificial Intelligence (AI) software for – Data Mining (clustering) Classification Forecasting NeuralWare collaborates with Customers and Partners to Embed Intelligent Neural Network Engines into NextGeneration Products and Systems © 2005 NeuralWare. All rights reserved. P-2 Introduction Characteristics of Neural Network Decision Support Systems Integrate Data and Analytics Adapt to Changing Conditions © 2005 NeuralWare. All rights reserved. P-3 Introduction Benefits of Neural Network Decision Support Systems Consistent Decisions Rapid Decisions Reproducible Decisions © 2005 NeuralWare. All rights reserved. P-4 Introduction Examples of Neural Network Decision Support Systems Medical Procedure Certification Crime Forecasting Grain Quality Assessments © 2005 NeuralWare. All rights reserved. P-5 Core Technology - Neural Networks Output Layer Target Target Decisions Based on Model Output Model Model Hidden Layer Input Layer Historic Data New Data Artificial Neural Networks are connected hierarchies of Artificial Neurons (also called Processing Elements) © 2005 NeuralWare. All rights reserved. P-6 Building Neural Networks © 2005 NeuralWare. All rights reserved. P-7 Evaluating Neural Network Performance © 2005 NeuralWare. All rights reserved. P-8 Evaluating Neural Network Performance © 2005 NeuralWare. All rights reserved. P-9 Deploying Neural Networks Application Server Architecture Server Contains Development and Run-Time Engine Browser-based wired or wireless remote PC clients do not employ NeuralWare technology NeuralWare Technology (Run-Time Engine/Models/FlashCode) embedded in Server © 2005 NeuralWare. All rights reserved. P-10 Deploying Neural Networks Distributed Intelligence Architecture Server Contains Development Engine Wired or wireless remote PC clients employ embedded NeuralWare technology (RunTime Engine/Models/FlashCode) © 2005 NeuralWare. All rights reserved. P-11 Case Study – Medical Procedure Certification Objectives Reduce Workload on Doctors and Registered Nurses Improve Responsiveness to Customers (faster decisions) Challenges No “Gold Standard” for decisions – even Doctors sometimes disagree Inconsistent data formats and labeling Process Used NeuralSight to build and evaluate ~ 30,000 Models in 3 weeks Developed prototype software to permit altering Model decision threshold © 2005 NeuralWare. All rights reserved. P-12 Case Study – Medical Procedure Certification Performance of best models (ranked by Average Classification Rate) for the Global model and CT and MRI Modality models © 2005 NeuralWare. All rights reserved. P-13 Case Study – Medical Procedure Certification © 2005 NeuralWare. All rights reserved. P-14 Case Study – Medical Procedure Certification Acquire/Validate Case Input Retrieve Metrics Metric Database Select/Execute Model Apply Thresholds Update Metrics Process Manually NO Approve Procedure? YES YES Selected for Audit? © 2005 NeuralWare. All rights reserved. DONE P-15 Case Study – Crime Forecasting Objectives Identify Patterns in Criminal Activity that indicate Potential Future Trouble Spots Redirect Police Resources to Focus on Areas where Serious Crime is expected to Increase Challenges Defining Crime Categories and Severity Levels Inconsistent data formats and labeling; missing or non-existent data Process Used NeuralSight to Build and Evaluate ~ 10,000 Models in 1 week On-going evaluation by researchers at Carnegie Mellon University © 2005 NeuralWare. All rights reserved. P-16 Case Study – Crime Forecasting © 2005 NeuralWare. All rights reserved. P-17 Case Study – Crime Forecasting How to Forecast Change in Crime Police know current crime levels Have allocated resources to respond to existing crimes Most valuable information for tactical level planning: Where is crime likely to have large increases next month? Forecast crime by area and calculate: Forecasted Change (t+1) = Forecast (t+1) – Actual (t) The Benefit – Better Allocation of Scarce Resources © 2005 NeuralWare. All rights reserved. P-18 Case Study – Crime Forecasting Forecasted Change for July © 2005 NeuralWare. All rights reserved. P-19 Case Study – Grain Quality Assessment Objectives Provide a Platform for rapidly and consistently assessing the quality of grain Maintain detailed records of tests and build foundation for data mining Challenges No “Gold Standard” for decisions – even experienced human inspectors are inconsistent Requires tedious work to identify wide variety of training data samples Process Used Predict and NeuralSight to Build and Evaluate many thousands of Models Now developing image database to support agriculture research © 2005 NeuralWare. All rights reserved. P-20 Case Study – Grain Quality Assessment An Instrument – and examples of seed images © 2005 NeuralWare. All rights reserved. P-21 Case Study – Grain Quality Assessment Many (more than 300) initial features per seed Predict Variable Selection found a much smaller set of features to use in building models The characteristics of grain that are important are difficult even for human inspectors to identify Multiple neural networks are used to make the hard decisions The value of wheat and other commodities depends on its quality – millions of dollars are at risk if quality decisions are incorrect! © 2005 NeuralWare. All rights reserved. P-22 What Have you Learned? Neural Networks make Powerful Decision Support Systems Human Judgment Determines the Cost/Benefit Tradeoff for Accuracy Know your Problem ! Neural Network Decisions are based on Learning Patterns Relationships in Historical Data are the basis for Current Action Know your Data ! © 2005 NeuralWare. All rights reserved. P-23 Thank You ! Jack Copper NeuralWare [email protected] Hiroshi Maruyama SET Software Co. Ltd. [email protected] © 2005 NeuralWare. All rights reserved. P-24