Introduction to AI and its medical applications: Crash Course for an audience with diverse scientific backgrounds

Donatella Cea, Helene Hoffmann, Marie Piraud
Proceedings of the Third Teaching Machine Learning and Artificial Intelligence Workshop, PMLR 207:7-11, 2023.

Abstract

Artificial intelligence (AI) and Machine Learning (ML) techniques have been developing more and more rapidly over the past few decades and teaching these methods can be very complicated even when students have good math and programming skills. Moreover, the background of the target group may be very diverse in terms of technical and coding skills, especially for a single introductory lecture. We describe here our experience in a three-hour crash course on introduction to AI and its medical applications, in which we alternated theoretical and practical sessions that could be engaging for students with different abilities and knowledge. The goals of the lecture were to demystify AI, introduce the challenges and current limitations of Deep Learning (DL), and present applications to the medical domain. The modularity of the course and choice of examples and tasks applied to the medical field interested the students who considered them authentic and relevant. The lesson has been positively evaluated by the students and their feedback identifies an NPS of 27 and an average of 8.2 over 10 when asked how likely they are to recommend the course to colleagues or friends.

Cite this Paper

BibTeX
@InProceedings{pmlr-v207-cea23a, title = {Introduction to AI and its medical applications: Crash Course for an audience with diverse scientific backgrounds}, author = {Cea, Donatella and Hoffmann, Helene and Piraud, Marie}, booktitle = {Proceedings of the Third Teaching Machine Learning and Artificial Intelligence Workshop}, pages = {7--11}, year = {2023}, editor = {Kinnaird, Katherine M. and Steinbach, Peter and Guhr, Oliver}, volume = {207}, series = {Proceedings of Machine Learning Research}, month = {19--23 Sep}, publisher = {PMLR}, pdf = {https://proceedings.mlr.press/v207/cea23a/cea23a.pdf}, url = {https://proceedings.mlr.press/v207/cea23a.html}, abstract = {Artificial intelligence (AI) and Machine Learning (ML) techniques have been developing more and more rapidly over the past few decades and teaching these methods can be very complicated even when students have good math and programming skills. Moreover, the background of the target group may be very diverse in terms of technical and coding skills, especially for a single introductory lecture. We describe here our experience in a three-hour crash course on introduction to AI and its medical applications, in which we alternated theoretical and practical sessions that could be engaging for students with different abilities and knowledge. The goals of the lecture were to demystify AI, introduce the challenges and current limitations of Deep Learning (DL), and present applications to the medical domain. The modularity of the course and choice of examples and tasks applied to the medical field interested the students who considered them authentic and relevant. The lesson has been positively evaluated by the students and their feedback identifies an NPS of 27 and an average of 8.2 over 10 when asked how likely they are to recommend the course to colleagues or friends.} }
Endnote
%0 Conference Paper %T Introduction to AI and its medical applications: Crash Course for an audience with diverse scientific backgrounds %A Donatella Cea %A Helene Hoffmann %A Marie Piraud %B Proceedings of the Third Teaching Machine Learning and Artificial Intelligence Workshop %C Proceedings of Machine Learning Research %D 2023 %E Katherine M. Kinnaird %E Peter Steinbach %E Oliver Guhr %F pmlr-v207-cea23a %I PMLR %P 7--11 %U https://proceedings.mlr.press/v207/cea23a.html %V 207 %X Artificial intelligence (AI) and Machine Learning (ML) techniques have been developing more and more rapidly over the past few decades and teaching these methods can be very complicated even when students have good math and programming skills. Moreover, the background of the target group may be very diverse in terms of technical and coding skills, especially for a single introductory lecture. We describe here our experience in a three-hour crash course on introduction to AI and its medical applications, in which we alternated theoretical and practical sessions that could be engaging for students with different abilities and knowledge. The goals of the lecture were to demystify AI, introduce the challenges and current limitations of Deep Learning (DL), and present applications to the medical domain. The modularity of the course and choice of examples and tasks applied to the medical field interested the students who considered them authentic and relevant. The lesson has been positively evaluated by the students and their feedback identifies an NPS of 27 and an average of 8.2 over 10 when asked how likely they are to recommend the course to colleagues or friends.
APA
Cea, D., Hoffmann, H. & Piraud, M.. (2023). Introduction to AI and its medical applications: Crash Course for an audience with diverse scientific backgrounds. Proceedings of the Third Teaching Machine Learning and Artificial Intelligence Workshop, in Proceedings of Machine Learning Research 207:7-11 Available from https://proceedings.mlr.press/v207/cea23a.html.

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