Cataract-LMM is a new multi-source dataset of 3000 annotated phacoemulsification videos enabling benchmarks for phase recognition, scene segmentation, interaction tracking, and automated skill assessment.
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Systematic benchmarking shows existing transcriptomic predictors for immune checkpoint inhibitor response have limited cross-cohort generalisability and inconsistent biomarker signals.
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Cataract-LMM Large-Scale Multi-Source Multi-Task Benchmark for Deep Learning in Surgical Video Analysis
Cataract-LMM is a new multi-source dataset of 3000 annotated phacoemulsification videos enabling benchmarks for phase recognition, scene segmentation, interaction tracking, and automated skill assessment.
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Transcriptomic Models for Immunotherapy Response Prediction Show Limited Cross-cohort Generalisability
Systematic benchmarking shows existing transcriptomic predictors for immune checkpoint inhibitor response have limited cross-cohort generalisability and inconsistent biomarker signals.