1. Faculdade de Medicina da Universidade do Porto Introdução à Medicina I "Artificial Intelligence in Medicine: a survey of interests and beliefs of health researchers from four backgrounds" Turma 7 Orientador: Pedro Pereira Rodrigues 9 de Dezembro de 2009

2. Contents ● Introduction ● Study design ● Methods ● Fluxogram ● Survey ● Expected Results ● Expected Difficulties

3. This second presentation will allow us to expose the main structure of our project. Having that, we may move on to the practical stage. Introduction

4. Artificial Intelligence (AI) is, in a modern definition, the study and design of intelligent agents, where an intelligent agent is a system that perceives its environment and takes actions which maximise chances of success. [1] [1] Bernstein RB, Curtis WN, Artificial Intelligence: New Research, 2009

5. Introduction Historical Context [2] ● The earliest work in medical AI dates back to the early 1970's; ● Over the next decade, the applications of AI in Medicine continued to grow; ● In 1980, a special subgroup of AI on medical applications was created; ● Since then, the field of AI in Medicine has spread all over the world and became robust. [2] SHORTLIFFE EH; AI in medicine comes of age: blossomig or languishing?; 2009; ICAART, 5-6

6. Introduction AI in Medicine [3] Nowadays, AI applications in Medicine are used to: ● Make diagnosis; ● Monitor patients; ● Create medical databases; ● Expand medical knowledge; ● Criticise and plan therapies,... [3] COIERA E.,Guide to Medical Informatics, the Internet and Telemedicine (Chapter 9 - Artificial Intelligence in Medicine: An Introduction); http://www.openclinical.org/aiinmedicine.html, accessed on October 2009

7. Introduction Impacts of AI ● The AIM field has already produced systems/programs/machines that demonstrate that the application of AI techniques to medical decision is a fruitful methodology. [4] ● A number of the programs already exhibit expert-level behavior on some medical problems. [4] ● Integrating AIM modules into the daily-routine software environment of our care providers gives us a great chance for maintaining and improving quality of care. [5] ● Last Presentation ● [4] SHORTLIFFE EH; AI in medicine comes of age: blossomig or languishing?; 2009; ICAART, 5-6 ● [5] ABBOD MF, LINKENS DA, DOUNIAS G, MAHFOUF M; Survey on the use of smart and adaptive engineering systems in medicine; Artif Intell Med; 26, 179-209; 2002

8. Research Question Is Artificial Intelligence relevant and valuable for current and future applications in Medicine?

9. Aim To survey the different interests and beliefs of four different types of health researchers about Artificial Intelligence in Medicine and its current and future applications

10. Specific Objectives ● Assess the different opinions across different types of health researchers: researchers of artificial intelligence in medicine, general clinical practitioners, critical care researchers and medical school deans. ● Identify the different applications/areas of impact/medical fields of AI in Medicine; ● Study the importance and the impact of AI in medical progress;

11. Specific Objectives Verify the contribution of medical researchers in the development of AI in Medicine Infer on the future application of AI in Medicine

12. Study design Observational and transversal study, using an online survey, answered by Directors of European Medical Schools, AIM researchers, Critical Care researchers and General Care researchers.

13. Methods 4 populations Directors of European Medical Schools Researchers of Artificial Intelligence Researchers of Critical Care Researchers of General Practice Journals AIM JAMIA SMMR Journals Critical Care Critical Care in Medicine Intensive Care Journals New England Lancet JAMA Contacts: 616 Contacts: 235 Contacts: 505 Contacts: 354

14. Methods Contacts Collection Journals: Search for e-mails of researchers in each area in the site of the journal in articles of the last 3 years Deans: Search for e-mails of directors of european medical schools in each university site Definition of each population

15. Methods ● Send out the survey; ● Get the answers; ● Statistical analysis of the data; ● Interpret results; ● Write report. SURVEY ARTICLE

16. Fluxogram Project's fluxogram

17. Fluxogram Data management - fluxogram

18. Methods Study variables: ● Demographic (nationality, age, medical specialization,…) ● Experience/impact (experiences related to AI in medicine, opinions, most important areas,...) ● ● Future (the future directions/uses of AI; areas where AI should be more developed,...)

19. Methods Statistical analysis ● Descriptive analysis of the study variables with the appropriate frequency measures; ● Possible associative analysis between factors with the appropriate associative measures: ● E.g.: researcher’s age with his opinion about the future of AI in medicine

20. Variables table ● Before making/organizing the survey, we designed tables so that we could better relate the different variables and define each question's objectivity and relevance. ● Tables for: ● - variables of experience/ impact; ● - future variables; ● - demographic variables; ● - specific academic backgrounds.

21. Variables table Demographic variables

22. Variables table Experience/impact

23. Variables table Future variables

24. Variables table Table for Physicians

25. Survey Introduction We are twelve students from the Faculty of Medicine of the University of Porto, Portugal, and we are surveying the different interests and beliefs of health researchers about Artificial Intelligence (AI) and its current and future applications in Medicine. Nowadays the application of AI in Medicine is a controversial topic – there is no single consensus about its positive and negative effects. However, the application of AI in Medicine has experimented a significant growth in the last few years; consequently, several questions rise about its relevance, utility, efficacy, effectiveness and efficiency. In a convergent perspective, this group of questions became a single interrogation, which is our research question: “Is Artificial Intelligence relevant and valuable for current and future applications in Medicine?”. To derive a valuable answer, we would like to ask you to kindly try to answer all the questions we have prepared. Thank you! Who we are What we are doing Brief facts about the main subject Our research question What we pretend

26. Survey Demographic questions Demographic questions Multiple choice Dicotomic Likert scale

27. Survey Demographic questions

29. Survey Impact/experience questions Impact/experience questions Multiple choice Dicotomic Likert scale

30. Survey Impact/experience questions

33. Survey Future questions Future questions Multiple choice Dicotomic Open answer

34. Survey Future questions

39. Expected results ● There will certainly be different opinions based on: ● - academic background; ● - medical specialization; ● - place of work. ● Researchers in Artificial Intelligence ● AIM Researchers will probably be more receptive in answering the questionnaire and also give highly favorable opinions in relation to the use of these systems in the future.

40. Expected results General Practice Researchers ● Will probably have a less beneficial view ● We believe that the availability to answer will depend mostly on the institution where physicians work and if AI resources are already available there.

41. Expected results Directors of European Medical Schools ● Should be receptive to the use of this technology since it is an excellent teaching and training tool for future physicians. ● It will all depend on the schools, countries and resources available.

42. Expected Results Critical Care Specialists ● Might have a good opinion about AI in Medicine as they work in emergency situations where it is important to be fast in knowing when it is more appropriate to continue diagnosis or begin therapy (this data might be easily obtained using AI). ● ● We hope to get a considerable amount of answers but highly related to researchers own specialization, since nowadays critical care is intimately related to AI.

43. Expected difficulties ● Language differences may discourage many from answering the survey. ● If response rate is very low, it may compromise the results of the work. ● Language differences makes the work of gathering contacts in European Universities difficult. ● Difficulties in obtaining the contacts of directors of medical schools in Europe.

44. Expected difficulties ● Difficulties in analysis and interpretation of the answers. ● Difficulties in the selection of the population to which we will send the questionnaire. ● Difficulties in the selection of variables to consider. ● Difficulties with the contacts obtained, since some of the emails may already be inactive.

45. Expected difficulties ● Some information contained from the Internet might not be correct, at least regarding contacts that were googled. ● Difficulties in creating questions for the survey. ● Delay in obtaining the answers. ● Difficulties with the creation of the database containing the contact details of researchers. ● People do not always show an interest in answering surveys.