Artificial Intelligence in Cancer Medicine

More information will be available soon.

Chairs 

M.S. Aapro, CH  - J. Gligorov, FR

Foreward

Medicine is a practice that uses different sciences.
When the management of serious diseases that can be life-threatening, we are constantly faced with two essential components of decision making that appeal to what is important to treat the disease on the one hand and what is valuable to the one that is treated on the other hand. If emotional intelligence refers to this valuable component, the amount of information that can be important regarding the treatment of a disease today exceeds our immediate and integrative analysis capacity.The integration of big data in clinical cancer research provides an unprecedented opportunity to integrate information and complex research outputs, which in turn demands 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 approaches in preclinical and translational cancer research has been increasing swiftly 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 cancer-research arena. Artificial intelligence has generated high expectations for improving cancer diagnosis, prognosis and therapy but has also underscored some of its inherent outstanding challenges, such as potential implicit biases in training datasets, data heterogeneity and the scarcity of external validation cohorts. Our scientific workshop has the aim to explore and discuss about different aspects of machine learning and cancer medicine. We would like to share our thoughts about this important field.

INVITED FACULTY
Giuseppe Curigliano, European Institute of Oncology / University of Milan, New Drugs for Innovative Therapies Division, Milan, IT
Joseph Gligorov, Hospital Tenon Ap-Hp, Paris, FR