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Artificial Intelligence in Cancer Care Educational Project

Background

Medicine is a practice that uses different sciences.
When managing serious, possibly life-threatening, diseases, we are constantly faced with two essential aspects of decision-making that appeal to what is important to treat the disease, on the one hand, and what is valuable to the person being treated, on the other. If artificial intelligence is applied to this valuable aspect, the amount of important information that can be gained for treating a disease today exceeds our capacity for immediate and integrative analysis. 

The integration of big data into clinical cancer research provides an unprecedented opportunity to integrate information and complex research outputs, which in turn requires powerful computational resources. Through its formidable analytical power, artificial intelligence holds the promise of transforming the way we study, diagnose and treat cancer.

The use of machine-learning in preclinical and translational cancer research has increased rapidly in recent years, bringing exciting progress in digital pathology and diagnostics and enriching foundational and drug-discovery research. From unfolding the intricacies of multi-omics and cellular phenotypes or extracting clinically relevant patterns to using behavioral data collected from wearable devices, machine learning is revolutionizing the arena of cancer research.

Artificial intelligence has given rise to great expectations for improving cancer diagnosis, prognosis and therapy but has also highlighted some of its inherent outstanding challenges, such as potential implicit biases in training datasets, data heterogeneity and the scarcity of external validation cohorts.

Project Goals

The development of knowledge and competences on integration of AI in Cancer Care Continuum: from diagnosis to clinical decision-making. 
The project will be supported by multimedia materials containing simulations or examples of AI applications in cancer care. 

Project Learning Objectives

  • To identify opportunities and challenges that may arise from the application of AI in Cancer Care Continuum
  • To share best practices in the application of AI in cancer diagnosis and treatment
  • To educate HCPs on the latest innovations of the application of AI to understand how it works on the clinical side
  • To raise cancer patients' awareness of AI in cancer care
  • To know implications of the new frontiers of AI in precision oncology

Project Target Group

HCPs - Cancer Patients Organisations – Oncologists - Researchers - Medical Companies - Cancer Institutes - Universities - Healthcare Public Authorities 

Project Approach and Outcomes

SPCC will carry out a multi-step project consisting of: 1) a series of Educational Webinars; 2) a Virtual Symposium on AI in cancer care.

All the sessions (free of charge and CME accredited) will be accessible to the audience by registering on SPCC's OncoCorner e-learning platform. The materials will remain available on-demand on OncoCorner.

Webinars

The first step of this project will consist of seven Educational Webinars, including multimedia examples and a panel discussion for each webinar on controversial topics, challenges and best practices of AI in cancer care. 

Webinars contents will be based on published data and focus on literature or experience examples. Regulatory issues (e.g., privacy, transparency) will be presented, where are relevant for specific topics or applications.

Seven Article Reports – one after each webinar - will be produced and published on the Cancerworld magazine.


WEBINAR 1 - AI in Cancer Care: an Overview
Live – 24 October 2022 – 17:30-19:00 CEST
Discussant: Eduardo Farina, BR
Speakers: Felipe Campos Kitamura, BR – Fabio Y. Moraes, CA – Aziz Nazha, US – Expert invited, not yet confirmed
Registrations are open via https://www.oncocorner.net/webinars/348

WEBINAR 2: AI Applications in Diagnosis
Live – 21 or 23 November 2022 – 17:30-19:00 CET
Discussant: Viktor Koelzer, CH
Speakers: Jeffrey David Iqbal, CH – Maria Rodriguez Martinez, CH – further Experts invited, not yet confirmed

WEBINAR 3: AI in Managing Clinical Data and Trials
Live – 5 or 14 December 2022 – 17:30-19:00 CET
Discussant: Olivier Michielin, CH
Speakers: Experts invited, not yet confirmed

WEBINAR 4: AI in Genomics and Reporting for Clinical Practice
Live – 25 January 2023 – 17:30-19:00 CET
Discussant: Pietro Valdastri, UK
Speakers: Elena De Momi, IT – Sara Moccia, IT – Keith Obstein, US – Dan Stoyanov, UK
Registrations are open via https://www.oncocorner.net/webinars/353

WEBINAR 5: AI in Robotic Surgery

Live – 15 or 27 February 2023 – 17:30-19:00 CET
Discussant: Bettina Ryll, SE
Speakers: Experts invited, not yet confirmed

WEBINAR 6: The Patient’s Perspective in AI
Live – 20 March 2023 – 17:30-19:00 CET
Discussant: Giancarlo Pruneri, IT
Speakers: Experts invited, not yet confirmed
Registrations are open via https://www.oncocorner.net/webinars/354

WEBINAR 7: Artificial Intelligence for Specific Tumours 
Live – 17 or 19 April 2023 – 17:30-19:00 CET
Discussant: Claudio Luchini, IT
Speakers: Antonio Pea, IT – Elliot Fishman, US – Eric Walk, US – Expert invited, not yet confirmed

Final timelines, faculties and further information about the webinars will be available soon.

Virtual Symposium

The Symposium will consist of a virtual round table with take-home messages presentations to be discussed between faculty and participants. It will summarize the main topics of the webinars (one for each area) with a special focus on multidisciplinary interaction.

An Article Report will be produced and published on the Cancerworld magazine.

 

Dates, faculty, programme and further information will be available soon.