A review of multi-instance learning assumptions

Multi-instance (MI) learning is a variant of inductive machine learning, where each learning example contains a bag of instances instead of a single feature vector. The term commonly refers to the supervised setting, where each bag is associated with a label. This type of representation is a natural fit for a number of real-world learning scenarios, including drug activity prediction and image classification, hence many MI learning algorithms have been proposed. Any MI learning method must relate instances to bag-level class labels, but many types of relationships between instances and class labels are possible. Although all early work in MI learning assumes a specific MI concept class known to be appropriate for a drug activity prediction domain; this ‘standard MI assumption’ is not guaranteed to hold in other domains. Much of the recent work in MI learning has concentrated on a relaxed view of the MI problem, where the standard MI assumption is dropped, and alternative assumptions are considered instead. However, often it is not clearly stated what particular assumption is used and how it relates to other assumptions that have been proposed. In this paper, we aim to clarify the use of alternative MI assumptions by reviewing the work done in this area

Influence of tumors on protective anti-tumor immunity and the effects of irradiation

Innate and adaptive immunity play important roles in the development and progression of cancer and it is becoming apparent that tumours can influence the induction of potentially protective responses in a number of ways. The prevalence of immunoregulatory T cell populations in the circulation and tumours of patients with cancer is increased, and the presence of these cells appears to present a major barrier to the induction of tumour immunity. One aspect of tumour-mediated immunoregulation which has received comparatively little attention is that which is directed towards natural killer (NK) cells, although evidence that the phenotype and function of NK cell populations are modified in patients with cancer is accumulating.Although the precise mechanisms underlying these localised and systemic immunoregulatory effects remain unclear, tumour-derived factors appear, in part at least, to be involved. The effects could be manifested by an altered function and/or via an influence on the migratory properties of individual cell subsets. A better insight into endogenous immunoregulatory mechanisms and the capacity of tumours to modify the phenotype and function of innate and adaptive immune cells might assist the development of new immunotherapeutic approaches and improve the management of patients with cancer.This article reviews current knowledge relating to the influence of tumours on protective anti-tumour immunity and considers the potential influence that radiation-induced effects might have on the prevalence, phenotype and function of innate and adaptive immune cells in patients with cancer