Predicting future falls in older people using natural language processing of general practitioners’ clinical notes
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DOI: 10.1093/ageing/afad046
Abstract: Abstract Background Falls in older people are common and morbid. Prediction models can help identifying individuals at higher fall risk. Electronic health records (EHR) offer an opportunity to develop automated prediction tools that may help… read more here.
Keywords: clinical notes; falls older; language processing; unstructured clinical ... See more keywords
Use of unstructured text in prognostic clinical prediction models: a systematic review
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DOI: 10.1093/jamia/ocac058
Abstract: Objective: This systematic review aims to assess how information from unstructured clinical text is used to develop and validate prognostic risk prediction models. We summarize the prediction problems and methodological landscape and assess whether using… read more here.
Keywords: systematic review; prediction models; prediction; text ... See more keywords
FarSight: Long-Term Disease Prediction Using Unstructured Clinical Nursing Notes
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DOI: 10.1109/tetc.2020.2975251
Abstract: Accurate risk stratification using patient data is a vital task in channeling prioritized care. Most state-of-the-art models are predominantly reliant on digitized data in the form of structured Electronic Health Records (EHRs). Those models overlook… read more here.
Keywords: farsight long; long term; disease; unstructured clinical ... See more keywords
An Evaluation of Pretrained BERT Models for Comparing Semantic Similarity Across Unstructured Clinical Trial Texts
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DOI: 10.3233/shti210848
Abstract: Processing unstructured clinical texts is often necessary to support certain tasks in biomedicine, such as matching patients to clinical trials. Among other methods, domain-specific language models have been built to utilize free-text information. This study… read more here.
Keywords: similarity; bert models; trial; trial texts ... See more keywords