Complex situations in lung cancer: multifocal disease, oligoprogression and oligorecurrence.

With the emergence of lung cancer screening programmes and newly detected localised and multifocal disease, novel treatment compounds and multimodal treatment approaches, the treatment landscape of non-small cell lung cancer is becoming increasingly complex. In parallel, in-depth molecular analyses and clonality studies are revealing more information about tumorigenesis, potential therapeutical targets and the origin of lesions. All can play an important role in cases with multifocal disease, oligoprogression and oligorecurrence.

Applications of Machine Learning in Palliative Care: A Systematic Review.

To summarize the available literature on using machine learning (ML) for palliative care practice as well as research and to assess the adherence of the published studies to the most important ML best practices. The MEDLINE database was searched for the use of ML in palliative care practice or research, and the records were screened according to PRISMA guidelines. In total, 22 publications using machine learning for mortality prediction (n = 15), data annotation (n = 5), predicting morbidity under palliative therapy (n = 1), and predicting response to palliative therapy (n = 1) were included.