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MEDICAL ERROR REPORTING AND ANALYSIS

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User Agent, Service Agent. Based on nature & source of intelligence ... User can exploit the learning ability of the agent to ease his job ... – PowerPoint PPT presentation

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Title: MEDICAL ERROR REPORTING AND ANALYSIS


1
MEDICAL ERROR REPORTING AND ANALYSIS
  • Vijaya Gotla
  • UmaDevi Bandaru
  • Lavanya Gundamaraju

2
MERA
  • A Decision support system
  • Two major functions
  • Error Report- The user reports an error by
    entering its details.
  • Error Analysis- User requests the information and
    statistics regarding a particular error.
  • Basically a research than an application
  • Incorporates
  • Distributed agent technology
  • Data mining and pattern matching
  • Machine learning

3
Software Agents
  • Inhabits some complex dynamic environment
  • Senses and acts autonomously in this environment
  • Realize a set of goals or tasks for which they
    are designed

4
Agent Characteristics
  • Autonomous
  • Intelligent
  • Adaptive/learning
  • Capable of reasoning
  • Mobile
  • Persistent
  • Goal oriented
  • Communicative/collaborative
  • Flexible
  • Open

5
Classification Of Agents
  • Based on nature of task performed
  • -User Agent, Service Agent
  • Based on nature source of intelligence
  • -Rule-based using user programmed rules
  • -Knowledge base programmed by knowledge engineer
  • -Machine Learning that program themselves
  • Based on location/mobility
  • -Fixed Agents, Mobile agents

6
Learning Agents
  • Can acquire and apply knowledge problem-solving
    methods
  • can learn, adjust that knowledge based on
    interaction with its environment
  • learns rules for classifying and archiving data

7
Machine learning
  • Machine learning makes data mining easier in case
    of large amounts of data
  • Learn a computational structure
  • Functions, problem solving systems, grammars and
    finite state machines.
  • LearningSupervised Unsupervised

8
ALGORITHMS
  • Predictive Methods
  • Classification
  • Regression
  • Deviation Detection
  • Descriptive Methods
  • Clustering
  • Association Rule Discovery
  • Sequential Pattern Discovery

9
Projects in Agent Technology
  • Interface agents for the electronic-mail domain
  • Monitors the actions of the user
  • Uses Memory based Reasoning algorithm.
  • Compares and matches
  • Predicts an action

10
Projects(Cont.)
  • Personalized Information Filtering
  • Build a set of adaptive autonomous interface
    agents that inhabit the user's computer
  • Uses the Feedback and Genetic algorithms
  • Options on Feedback
  • Creates new profile
  • Directs to existing profile

11
Inference
  • Agents are autonomous programmed components
  • Agents can be used to monitor user actions
  • User can exploit the learning ability of the
    agent to ease his job
  • Agents can collaborate with each other

12
What is in MERA
  • Distributed, Component based, Agent technology
  • Learning Agent
  • Association Based Algorithm
  • Collaboration in Agents
  • Not Peer Agents

13
System Framework

Service Agent
DB
User Agent
14
Drawbacks
  • Internal state of the agent is abstract to the
    user
  • Application specific Agent development
  • Agent Reusability
  • Slow Learning curve
  • Require sufficient amount of time before they can
    be of any use
  • Greatest drawbacks to machine learning is that
    knowledge acquired while learning one skill does
    not enhance the learning of other related skills

15
Thank You.
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