Oncocorner

Online Course
on demand

May
2023

AI, Technology & Innovation

Artificial Intelligence in Cancer Care Online Symposium

Chairs

Aleksandra Filipovic, UK - Dimitris Kalogeropoulos, UK

Date

25 May 2023

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.

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

Target Group

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

Course Format

The course will be held online with the participation of world-renowned experts, some of them already involved in webinars.

It will be free of charge and can be accessed by registering on SPCC's OncoCorner e-learning platform. The material will remain available on-demand.

Continuing Medical Education accreditation

Application for CME accreditation has been submitted to the Accreditation Council of Oncology in Europe (ACOE).

The programme was recognised as being of high quality from both a scientific and didactic point of view and was awarded 2 CME credits.

Participants will be issued a certificate of attendance (minimum attendance: 75% of the entire course). An online evaluation questionnaire and learning assessment test will need to be completed in order to get the certificate that will be issued by email.

Acknowledgements

Sharing Progress in Cancer Care wishes to express its appreciation to AstraZeneca, Novartis and Roche for their indipendent support.

25/05/2023 13:00 CEST

Programme

Expert: Kölzer Viktor, CH

Expert: Luchini Claudio, IT

Expert: Pruneri Giancarlo, IT

Expert: Valdastri Pietro, UK

25/05/2023 15:25 CEST

Closing remarks

Chair: Filipovic Aleksandra, UK

Chair: Kalogeropoulos Dimitris, UK

Chen Tim

Scientist at Foundation Medicine, Boston, USA

Farina Eduardo

UNIFESP (Federal University of São Paulo) and Diagnósticos da América SA (DASA), Sao Paolo, Brazil

Filipovic Aleksandra

Imperial College London, London, United Kingdom

Kalogeropoulos Dimitris

Chief Executive at the Global Health & Digital Innovation Foundation, London, United Kingdom

Keefe Dorothy

CEO at Cancer Australia, Surry Hills NSW, Australia

Kölzer Viktor

Attending Pathologist, Institute of Pathology and Molecular Pathology - Assistant Professor and Lead for Digital Pathology, University of Zürich, Zürich, Switzerland

Luchini Claudio

Diagnostics and Public Health Dept., Section of Pathology, and ARC-Net Research Center, University and Hospital Trust of Verona, Verona, Italy

Pruneri Giancarlo

IRCCS National Cancer Institute, Milan, Italy

Valdastri Pietro

Professor and Chair in Robotics and Autonomous Systems, University of Leeds, Leeds, United Kingdom

This material is part of Educational Project:

2022 - Artificial Intelligence in Cancer Care Educational Project

Go to Educational Project