Markus Nilsson Dept. Of Computer Science and Engineering Mälardalen University Västerås, Sweden.

Slides:



Advertisements
Similar presentations
Machine Learning Instance Based Learning & Case Based Reasoning Exercise Solutions.
Advertisements

Expert Systems Reasonable Reasoning An Ad Hoc approach.
New Technologies Supporting Technical Intelligence Anthony Trippe, 221 st ACS National Meeting.
Universiteit Maastricht Standards and Distance Education Peter A.J. Bouhuijs Professor in Health Science Education.
Chapter Eleven Artificial Intelligence II: Operational Perspective.
Rule Based Systems Alford Academy Business Education and Computing
NEUROLOGY DIAGNOSIS SYSTEM Under supervision of Prof. Dr. Shashidhar Ram Joshi (Mentor: Bikram Lal Shrestha) A Final Presentation on Presented by: Badri.
Artificial Intelligence and Case-Based Reasoning Computer Science and Engineering Mälardalen University Västerås, Mikael Sollenborn, CSL,
Markus Nilsson Dept. Of Computer Science and Engineering Mälardalen University Västerås, Sweden.
Bayesian Belief Networks
Expert Report By Prof. Rayko Genchev Raykov, Ph.D. On the research of experts’ views on the problems considered in the project “New Approach in Technology.
Automated Changes of Problem Representation Eugene Fink LTI Retreat 2007.
Introduction to Artificial Neural Network and Fuzzy Systems
GL12 Conf. Dec. 6-7, 2010NTL, Prague, Czech Republic Extending the “Facets” concept by applying NLP tools to catalog records of scientific literature *E.
CBR in Medicine Jen Bayzick CSE435 – Intelligent Decision Support Systems.
Copyright R. Weber INFO 629 Concepts in Artificial Intelligence Fall 2004 Professor: Dr. Rosina Weber.
Knowledge Acquisition from Game Records Takuya Kojima, Atsushi Yoshikawa Dept. of Computer Science and Information Engineering National Dong Hwa University.
Xiaoying Sharon Gao Mengjie Zhang Computer Science Victoria University of Wellington Introduction to Artificial Intelligence COMP 307.
Knowledge representation
Division of Population Health Sciences Royal College of Surgeons in Ireland Coláiste Ríoga na Máinleá in Éirinn Developing a web-based international register.
Image Pattern Recognition The identification of animal species through the classification of hair patterns using image pattern recognition: A case study.
RECENT DEVELOPMENTS OF INDUCTION MOTOR DRIVES FAULT DIAGNOSIS USING AI TECHNIQUES 1 Oly Paz.
Medical Bioinformatics Prof:Rui Alves Dept Ciencies Mediques Basiques, 1st.
International Conference on Machine Learning and Cybernetics, Vol. 1, p.p July, Research on a Fuzzy Multi-Objective Decision Model.
Assoc. Prof. Abdulwahab AlSammak. Course Information Course Title: Artificial Intelligence Instructor : Assoc. Prof. Abdulwahab AlSammak
1 Discovery of Temporal Patterns in Course-of-Disease Medical Data Jorge C. G. Ramirez Ph.D. Candidate Lynn L. Peterson and Diane J. Cook Supervising Professors.
Computing & Information Sciences Kansas State University Paper Review Guidelines KDD Lab Course Supplement William H. Hsu Kansas State University Department.
Knowledge Representation of Statistic Domain For CBR Application Supervisor : Dr. Aslina Saad Dr. Mashitoh Hashim PM Dr. Nor Hasbiah Ubaidullah.
1 Pattern Recognition Pattern recognition is: 1. A research area in which patterns in data are found, recognized, discovered, …whatever. 2. A catchall.
School of Engineering and Computer Science Victoria University of Wellington Copyright: Peter Andreae, VUW Image Recognition COMP # 18.
1 The main topics in AI Artificial intelligence can be considered under a number of headings: –Search (includes Game Playing). –Representing Knowledge.
Supervisor: Fearghal Morgan Analog Devices: Ray Carter Dept. Electronic Engineering NUIG 23 April 2008 Software Driver for ADV7800 Video Decoder Nóirín.
Generic Tasks by Ihab M. Amer Graduate Student Computer Science Dept. AUC, Cairo, Egypt.
Chapter 4 Decision Support System & Artificial Intelligence.
Revised MS Program in Computer Science INFORMATION AND COMPUTER SCIENCE DEPARTMENT December 2002.
Software Engineering Education Framework Sun-Myung Hwang Computer Engineering Dept, Daejeon University, Republic of Korea Abstract. Software.
Artificial Intelligence, Expert Systems, and Neural Networks Group 10 Cameron Kinard Leaundre Zeno Heath Carley Megan Wiedmaier.
ARTIFICIALINTELLIGENCE ARTIFICIAL INTELLIGENCE EXPERT SYSTEMS.
Introduction to Artificial Intelligence CS 438 Spring 2008.
NOTICE! These materials are prepared only for the students enrolled in the course Distributed Software Development (DSD) at the Department of Computer.
Case Based Reasoning Project Presentation Presenter: Madan Bharadwaj Instructor: Dr. Avelino Gonzalez.
Technologies Derek Middleton, Qualification Development Manager Scottish Qualifications Authority.
O NCE TRADING BEGINS, PLEASE ALLOW IT TO TRADE O NCE TRADING BEGINS, PLEASE ALLOW IT TO TRADE B E REALISTIC WITH YOUR EXPECTATIONS B E REALISTIC WITH.
Modeling Security-Relevant Data Semantics Xue Ying Chen Department of Computer Science.
Transforming lives through learning Technologies Advice and guidance developed 2011/12 Computing Science Starting from Scratch, National 4 Hardware: Exemplar.
R&D Operation Best Practice for Start Up Start a Business And Change the world Alfred Boediman, Ph.D.
Digital Data Collections in Biology Collaborative Expedition Workshop November 8, 2005 Arlington, Virginia Chris Greer Program Director National Science.
FNA/Spring CENG 562 – Machine Learning. FNA/Spring Contact information Instructor: Dr. Ferda N. Alpaslan
Chapter 12. Probability Reasoning Fall 2013 Comp3710 Artificial Intelligence Computing Science Thompson Rivers University.
Business Analytics Several odds and ends Copyright © 2016 Curt Hill.
These materials are prepared only for the students enrolled in the course Distributed Software Development (DSD) at the Department of Computer.
Brief Intro to Machine Learning CS539
Inexact Reasoning 2 Session 10
Artificial Intelligence
Deep Learning Amin Sobhani.
Lecture #1 Introduction
CHAPTER 1 Introduction BIC 3337 EXPERT SYSTEM.
Organization and Knowledge Management
Inexact Reasoning 2 Session 10
CS 4100 Artificial Intelligence
What is Pattern Recognition?
Options for Stage 3 16th March 2018.
CSSE463: Image Recognition Day 20
Taxonomy of Problem Solving and Case-Based Reasoning (CBR)
An Autonomous System View To Apply Machine Learning
Course Outline Advanced Introduction Expert Systems Topics Problem
Machine Learning Course.
Prepared by: Mahmoud Rafeek Al-Farra
Probabilistic Reasoning
Knowledge-based Systems
Presentation transcript:

Markus Nilsson Dept. Of Computer Science and Engineering Mälardalen University Västerås, Sweden

Retrospect Air-Pas RBR Require Expert incomplete Electronics, A/D converters Patient Expert lpr Report Expert System PC Illustrations adapted from Peter Funk

The PIMP Project

Research findings New algoritms New combinations of AI methods Unexplored field Research materialized into products Completely new AI method?

Contributions 2-3 papers until the Lic. Times 2 for the PhD Healthier population Higher standard and reputation GNP Best Paper Award

Got Time? Project stages: 1.Augment the existing system Analysing current patient data Construct a patient/system model Build a prototype Replace/augment old system permanently 2.Aquire deeper knowledge 3.Build new system

Got Knowledge? Strategy: Many courses in the beginning to aquire necessary knowledge. No courses left == no project interrupt. ICCBR, IJCAI,ECCBR and other conferences. Contact others in the area. Courses: AI adv. CBR Machine Learning Clustering Neural Nets Research Methology Science Planning

Got sugar.. daddy? Identify and classify patients Build test and default cases Implement diagnosis reasoner Find best method for curve identification Implement curve recognition Build classification library Implement classification reasoner Implement report handler implement graphics engine add domain rules sleep

Summary I will probably pull this off