adenocarcinoma of the lung
PulseAugur coverage of adenocarcinoma of the lung — every cluster mentioning adenocarcinoma of the lung across labs, papers, and developer communities, ranked by signal.
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New MIL method improves rare joint molecular phenotype prediction in cancer
Researchers have developed a novel weakly supervised method called State-Aware Interaction MIL to improve the prediction of rare joint molecular phenotypes in colorectal cancer and lung adenocarcinoma. This approach eff…
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New method offers efficient model testing via kernelized Stein discrepancy
Researchers have developed a new, computationally efficient method for assessing the adequacy of statistical and machine learning models, particularly those with intractable normalizing constants. This approach utilizes…
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AI models in pathology gain robustness through new benchmarking and artifact generation techniques
Two new research papers explore methods for improving the reliability and robustness of AI models in computational pathology. The first paper, "Reliable Benchmarking of Artifact Detection in Computational Pathology," pr…
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New RL framework enables rapid tumor segmentation on whole-slide images
Researchers have developed a novel end-to-end reinforcement learning framework for segmenting tumors directly on whole-slide images (WSIs). This approach treats the WSI as an interactive, hierarchical environment, allow…
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AI maps lung cancer growth patterns using visual vocabulary
Researchers have developed a novel weakly supervised Bag-of-Visual-Words (BoVW) pipeline to map lung adenocarcinoma growth patterns from whole slide images. This method utilizes frozen foundation model embeddings to lea…
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Foundation models aid lung cancer growth pattern prediction with attention-based learning
Researchers have developed an attention-based multiple instance learning (ABMIL) framework to predict lung adenocarcinoma growth patterns from whole slide images. This method reduces the need for extensive annotations b…