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

Slides:



Advertisements
Similar presentations
Introduction to Information System
Advertisements

Expert Systems An expert system is a computer program that is designed to hold the accumulated knowledge of one or more domain experts.
EXPERT SYSTEMS AND KNOWLEDGE REPRESENTATION Ivan Bratko Faculty of Computer and Info. Sc. University of Ljubljana.
ICT and medicine IT & C Department AP - Secretariat.
© C. Kemke1Expert Systems Tasks COMP 4200: Expert Systems Dr. Christel Kemke Department of Computer Science University of Manitoba.
Diagnosing – Critical Activity HINF Medical Methodologies Session 7.
NEUROLOGY DIAGNOSIS SYSTEM Under supervision of Prof. Dr. Shashidhar Ram Joshi (Mentor: Bikram Lal Shrestha) A Final Presentation on Presented by: Badri.
Artificial Intelligence MEI 2008/2009 Bruno Paulette.
Eran Chinthaka & Jaliya Ekanayake Class Project for: Knowledge Based Computing (B552)
Chapter 11 Artificial Intelligence and Expert Systems.
DSS: Decision Support Systems and AI: Artificial Intelligence
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.
Obstetrics And Gynecology Curriculum
EXPERT SYSTEMS Part I.
SIGDIG – Signal Discrimination for Condition Monitoring A system for condition analysis and monitoring of industrial signals Collaborative research effort.
DSS: Decision Support Systems and AI: Artificial Intelligence
Extracting Test Cases by Using Data Mining; Reducing the Cost of Testing Andrea Ciocca COMP 587.
ICT in Healthcare Expert Systems.
Research. Broad research, from science to community planning Research involves more than 3,000 staff members –More than 600 people belong to the Faculty.
CBR in Medicine Jen Bayzick CSE435 – Intelligent Decision Support Systems.
“Put the Power of Predictive Analytics in the Hands of Clinical Researchers” Filippos Katsampouris Marketing Manager Healthcare & Pharmaceutical Accounts.
Expert System Note: Some slides and/or pictures are adapted from Lecture slides / Books of Dr Zafar Alvi. Text Book - Aritificial Intelligence Illuminated.
Home Health Care and Assisted Living Professor John A. Stankovic Department of Computer Science University of Virginia.
Case-based Adaptations in Medicine Focusing on Hypothyroidism Rainer Schmidt, Olga Vorobieva, Lothar Gierl Institute for Medical Informatics and Biometry.
 Expanding roles of I.S.  Types of I.S  Transaction Processing  Record Keeping  Tradional Accounting applications.
Artificial Intelligence
Course Instructor: K ashif I hsan 1. Chapter # 2 Kashif Ihsan, Lecturer CS, MIHE2.
RITRIT Biomedical Engineering Department of Chemical and Biomedical Engineering Kate Gleason College of Engineering Rochester Institute of Technology.
The academic sector – a part of innovation development.
ICT and medicine. Objectives The uses of ICT in medicine The uses of ICT in medicine in patient records, medical equipments, internet devices…etcin patient.
Overall course structure AI Artificial Intelligence ( A modern approach ) AI-2 Spring semester TDT4171 Methods in artificial intelligence AI-1 Fall semester.
What is an Expert System? An expert system is a program implemented in a computer which is designed to mimic the problem-solving ability of a specialist.
CSC 554: Knowledge-Based Systems Part-1 By Dr. Syed Noman Hasany Assistant Professor, CoC Qassim University.
Research In the service of humanity, for the society of tomorrow.
Healthcare Process Modelling by Rule Based Networks Han Liu First Year PhD Student Alex Gegov, Jim Briggs, Mohammed Bader PhD Supervisors.
Artificial Intelligence and Expert Systems. ARTIFICIAL INTELLIGENCE (AI) is the science of R L Being able to Ability to solve a problem.
Bioinformatics Masters programs in Stockholm and Sweden Stockholm Bioinformatics Center Stockholm University and Royal Institute of Technology (and Karolinska.
1 Computer Group Engineering Department University of Science and Culture S. H. Davarpanah
Knowledge Learning by Using Case Based Reasoning (CBR)
Artificial intelligence
Lecture 11 Introduction to Information Systems Lecture 12 Objectives  Describe an information system and explain its components  Describe the characteristics.
Fundamentals of Information Systems, Third Edition1 The Knowledge Base Stores all relevant information, data, rules, cases, and relationships used by the.
Artificial Intelligence, Expert Systems, and Neural Networks Group 10 Cameron Kinard Leaundre Zeno Heath Carley Megan Wiedmaier.
Clinical Decision Support 1 Historical Perspectives.
ARTIFICIALINTELLIGENCE ARTIFICIAL INTELLIGENCE EXPERT SYSTEMS.
Introduction to Artificial Intelligence CS 438 Spring 2008.
Expert Systems. Expert systems Also known as ‘Knowledge-based systems’:  Computer programs that attempt to replicate the performance of a human expert.
Clinical Decision Support Systems Dimitar Hristovski, Ph.D. Institute of Biomedical.
Access Control for Dynamic Virtual Organisations Duncan Russell, Peter Dew & Karim Djemame University of Leeds.
 Work with top experts  World-class experimental facilities  High-performance computing facilities  International travel  Pleasant work environment.
Of An Expert System.  Introduction  What is AI?  Intelligent in Human & Machine? What is Expert System? How are Expert System used? Elements of ES.
ITEC 1010 Information and Organizations Chapter V Expert Systems.
Ch  ICT is used in many ways in the provision and management of healthcare services:  Hospital administration  Medical training  Maintenance.
Artificial Intelligence, simulation and modelling.
MSP Regional Meeting: NIH Resources to Support STEM Education Bruce A. Fuchs, Ph.D., Director Office of Science Education National Institutes of Health,
Experiments in respiration, RQ and alternative substrates.
Survey on Expert System Seung Jun Lee Dept. of Nuclear and Quantum Engineering KAIST Mar 3, 2003.
Artificial Intelligence: Applications
Organization and Knowledge Management
Introduction Characteristics Advantages Limitations
3.3. Case-Based Reasoning (CBR)
DSS: Decision Support Systems and AI: Artificial Intelligence
Sport And Spine Center Presents By Denise Campbell
Karolinska Institutet
Taxonomy of Problem Solving and Case-Based Reasoning (CBR)
Computerized Decision Support for Medical Imaging
Case-Based Reasoning BY: Jessica Jones CSCI 446.
Expert Knowledge Based Systems
W. Wakeland 1,2, J. Fusion 1, B. Goldstein 3
Presentation transcript:

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

Project X? Industrial funded PhD Student Funding: KK-stiftelsen50% Stress Medical Innovation & Development AB 40% Mälardalen University10%

A Medical System Analyze measurements Diagnose patient status Predict future symptoms

Related research Stress medicine: One group in Israel and one in Texas, USA. AI - CBR:  Janet L. Kolodner, Georgia Institute of Technology, USA  Ian Watson, University of Auckland, New Zealand.  Roger C. Schank, Institute for the Learning Science, Northwestern University, USA

Related projects No similar projects exists combining stress medicine and AI. Medical diagnosis and CBR: TROPIX -Tropical disease diagnosis and treatment Medical diagnosis and RBR: MYCIN, PUFF...

Facts & Figures A spin-off company from Karolinska Institutet Focused on development Specialized in diagnosing and treatment of stress related diseases Located: Karolinska Institutet, Stockholm Uppsala Science park, Uppsala Aprox. 6 employees One product released – AirPas(2001)

Current system Air-Pas Sensors, electronics, pc, expert system Rules derived from the company expert, PhD Bo von Schéele Automatically generates a report Electronics, A/D converters Patient Expert lpr Report Expert System PC Illustrations adapted from Peter Funk

AirPas Measuring: Oxygen saturation (Sa0 2 ) Blood Volume Pulse (BVP) Heart Rate (HR) Carbon dioxide levels (CO 2 )

AirPas Calculating: Top level of CO 2, (ETCO2) Respiration Rate (RR) Collecting data from several sessions under different conditions

Problems Limited ability to diagnose Maintenance & Brittleness Only Bo can do a complete diagnose Domain limitations – e.g. Yoga Supervisor required

Research Challenges 1.Eliminate the need for an expert 2.Produce more accurate diagnosis 3.Suggest treatment 4.Solve problems outside the knowledge of current system 5.Handle unknown situations 6.Learn and improve 7.Share the knowledge

Summary Stressmedicine and AirPas. Rule Based reasoning not sufficient Little related research (CBR & Medicine).