{"entity":{"id":"abmil","kind":"term","name":"Attention-based multiple-instance learning (ABMIL, CLAM)","aka":["ABMIL","attention-based MIL","attention-based multiple instance learning","multiple-instance learning","multiple instance learning","MIL","CLAM","attention pooling","slide-level aggregation","weakly supervised slide classification"],"tldr":"Attention-based multiple-instance learning gives each tile of a slide a learned weight and sums the weighted tile vectors into one slide vector, so a slide-level label can train the model and the weights show which regions mattered.","summary":"In multiple-instance learning the learner receives labelled bags of instances rather than labelled instances (Wikipedia). Ilse, Tomczak and Welling proposed pooling the instances with a small attention network, and Lu and colleagues' CLAM applied it to whole-slide images with clustering constraints for data-efficient, weakly supervised pathology. It is the default slide encoder head over frozen tile embeddings, the interface most pathology pipelines expose, and its attention maps are read as heat maps of evidence.","asOf":"2026-09-24","wikipedia":"https://en.wikipedia.org/wiki/Multiple_instance_learning","links":[{"label":"Ilse, Tomczak and Welling, Attention-based deep multiple instance learning (arXiv 2018)","url":"https://arxiv.org/abs/1802.04712"},{"label":"Lu et al., CLAM (Nature Biomedical Engineering 2021)","url":"https://doi.org/10.1038/s41551-020-00682-w"},{"label":"Wikipedia","url":"https://en.wikipedia.org/wiki/Multiple_instance_learning"}],"tags":["cansim-terms"],"related":["cancer-ai-vocabulary"],"cancers":[],"sections":[],"technologies":[],"targets":[],"drugs":[],"companies":[],"institutions":[],"pathways":[],"terms":["tile-patch-encoding","transformer-architecture","pathology-foundation-models"],"trials":[],"people":[],"bottlenecks":[],"keyPapers":[],"journals":[],"dependsOn":[],"notes":["Listed in the CanSim terms map 1.0.0 (docs/onco/terms.json, generated 2026-09-24), CC BY 4.0, attribution: CanSim project, an open, public-data-first cancer foundation-model programme; CanSim page path /terms/abmil."],"provenance":{"editedBy":"OnCo CanSim terms wave (Wikipedia summaries, standards and project pages, GDC and FDA pages, Europe PMC)","editedOn":"2026-09-24","note":"CanSim terms map 1.0.0 (docs/onco/terms.json, generated 2026-09-24), CC BY 4.0, attribution: CanSim project, an open, public-data-first cancer foundation-model programme"},"category":"Methods and models"},"route":"/terms/abmil/","neighbours":{"term":[{"id":"cancer-ai-vocabulary","kind":"term","name":"Cancer AI vocabulary (CanSim terms map)","route":"/terms/cancer-ai-vocabulary/"},{"id":"pathology-foundation-models","kind":"term","name":"Pathology foundation models: UNI, UNI2, Virchow2, CTransPath, CONCH, TITAN","route":"/terms/pathology-foundation-models/"},{"id":"tile-patch-encoding","kind":"term","name":"Tile and patch encoding of slides","route":"/terms/tile-patch-encoding/"},{"id":"transformer-architecture","kind":"term","name":"Transformer and attention","route":"/terms/transformer-architecture/"}]}}