BMLLC 2022

Lung cancer is one of the most commonly diagnosed cancers and is the leading cause of cancer-related deaths The .most common histological subtype is non-small-cell lung carcinoma, accounting for 85% of all lung cancer cases. Advanced NSCLC is more likely to metastasize, leading to severe symptoms and a decrease in overall survival. The presence of distant metastases is one of the most predictive factors of poor prognosis. The main goal of this session is to present original models and methods, which support analysis of clinical, molecular and imaging data and aim at better prediction of spread and colonization of tumor cells to distant organs, with emphasis on the most common subtype of lung cancer - non-small-cell lung carcinoma (NSCLC). Since the metastatic tumor is mainly incurable, due to its resistance to treatment, we expect to be able to discuss the urgent biological and clinical question: how, when, and where the primary tumor will spread to distant locations. The proposed session is supposed to include interdisciplinary research employing methods from machine learning, data analysis, bio-mathematical modeling, image processing, bioinformatics and systems biology, with strong support from clinical, molecular and biomedical images data. It will give opportunity to present a new framework of data integration and analysis and novel algorithms that will support interdisciplinary research. We want to offer an opportunity for researchers and practitioners to identify new promising research directions as well as to publish recent advances in this area. The scope of the BMLLC 2022 includes, but is not limited to the following topics:

Special Session on Bio-modeling and Machine Learning in Prediction of Metastasis in Lung Cancer

Special Session Organizers

Objectives and topics

ACIIDS 2022 important dates