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A validated natural language processing algorithm for brain imaging phenotypes from radiology reports in UK electronic health records.

, , , , , and . BMC Medical Informatics Decis. Mak., 19 (1): 184:1-184:11 (2019)

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Development of a Deep Learning Method to Identify Acute Ischemic Stroke Lesions on Brain CT., , , , , , , , and . CoRR, (2023)Machine learning of neuroimaging to diagnose cognitive impairment and dementia: a systematic review and comparative analysis., , , , , , , , , and 4 other author(s). CoRR, (2018)Text mining brain imaging reports., , , , , and . J. Biomed. Semant., 10 (1): 23:1-23:11 (2019)A Comparison of Cranial Cavity Extraction Tools for Non-contrast Enhanced CT Scans in Acute Stroke Patients., , , , , , and . Neuroinformatics, 20 (3): 587-598 (2022)A validated natural language processing algorithm for brain imaging phenotypes from radiology reports in UK electronic health records., , , , , and . BMC Medical Informatics Decis. Mak., 19 (1): 184:1-184:11 (2019)Understanding the performance and reliability of NLP tools: a comparison of four NLP tools predicting stroke phenotypes in radiology reports., , , , , , , , , and 8 other author(s). Frontiers Digit. Health, (March 2023)Diffusion Models for Counterfactual Generation and Anomaly Detection in Brain Images., , , , and . CoRR, (2023)ACAT: Adversarial Counterfactual Attention for Classification and Detection in Medical Imaging., , , , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 10153-10169. PMLR, (2023)