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pro vyhledávání: '"Mary, M."'
Advances in large language models (LLMs) have encouraged their adoption in the healthcare domain where vital clinical information is often contained in unstructured notes. Cancer staging status is available in clinical reports, but it requires natura
Externí odkaz:
http://arxiv.org/abs/2404.13149
Autor:
Lucas, Mary M., Wang, Xiaoyang, Chang, Chia-Hsuan, Yang, Christopher C., Braughton, Jacqueline E., Ngo, Quyen M.
Fairness of machine learning models in healthcare has drawn increasing attention from clinicians, researchers, and even at the highest level of government. On the other hand, the importance of developing and deploying interpretable or explainable mod
Externí odkaz:
http://arxiv.org/abs/2404.03833
Cancer stage classification is important for making treatment and care management plans for oncology patients. Information on staging is often included in unstructured form in clinical, pathology, radiology and other free-text reports in the electron
Externí odkaz:
http://arxiv.org/abs/2404.01589
Stepped wedge cluster randomized trials (SW-CRTs) are a form of randomized trial whereby clusters are progressively transitioned from control to intervention, with the timing of transition randomized for each cluster. An important task at the design
Externí odkaz:
http://arxiv.org/abs/2312.13097
The two-stage preference design (TSPD) enables the inference for treatment efficacy while allowing for incorporation of patient preference to treatment. It can provide unbiased estimates for selection and preference effects, where a selection effect
Externí odkaz:
http://arxiv.org/abs/2310.11603