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Francesca Sasanelli, Khang Duy Ricky Le, Samuel Boon Ping Tay, Phong Tran and Johan W. Verjans
The advent of many popular commercial forms of natural language processing tools has changed the way we can utilise digital technologies to tackle problems with big data. The objective of this review is to evaluate the current research and landscape of n...
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Yijun Shao, Kaitlin Todd, Andrew Shutes-David, Steven P. Millard, Karl Brown, Amy Thomas, Kathryn Chen, Katherine Wilson, Qing T. Zeng and Debby W. Tsuang
The application of natural language processing and machine learning (ML) in electronic health records (EHRs) may help reduce dementia underdiagnosis, but models that are not designed to reflect minority populations may instead perpetuate underdiagnosis. ...
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Rezaul K. Khandker, Md Rakibul Islam Prince, Farid Chekani, Paul Richard Dexter, Malaz A. Boustani and Zina Ben Miled
Patient-reported (PRO) and clinician-reported (CRO) outcomes are assessment instruments that are completed by patients and trained healthcare professionals, respectively. A PRO is a report of the direct experience of the patient with a given disease cond...
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Cyrille YetuYetu Kesiku, Andrea Chaves-Villota and Begonya Garcia-Zapirain
The classification of biomedical literature is engaged in a number of critical issues that physicians are expected to answer. In many cases, these issues are extremely difficult. This can be conducted for jobs such as diagnosis and treatment, as well as ...
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Akram Mustafa and Mostafa Rahimi Azghadi
Machine learning (ML) has been slowly entering every aspect of our lives and its positive impact has been astonishing. To accelerate embedding ML in more applications and incorporating it in real-world scenarios, automated machine learning (AutoML) is em...
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Usman Naseem, Matloob Khushi, Shah Khalid Khan, Kamran Shaukat and Mohammad Ali Moni
An enormous amount of clinical free-text information, such as pathology reports, progress reports, clinical notes and discharge summaries have been collected at hospitals and medical care clinics. These data provide an opportunity of developing many usef...
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Asra Fatima, Ying Li, Thomas Trenholm Hills and Massimo Stella
Most current affect scales and sentiment analysis on written text focus on quantifying valence/sentiment, the primary dimension of emotion. Distinguishing broader, more complex negative emotions of similar valence is key to evaluating mental health. We p...
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Eyal Klang, Matthew A. Levin, Shelly Soffer, Alexis Zebrowski, Benjamin S. Glicksberg, Brendan G. Carr, Jolion Mcgreevy, David L. Reich and Robert Freeman
The Epic electronic health record (EHR) is a commonly used EHR in the United States. This EHR contain large semi-structured ?flowsheet? fields. Flowsheet fields lack a well-defined data dictionary and are unique to each site. We evaluated a simple free-t...
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Oguz Akbilgic, Ramin Homayouni, Kevin Heinrich, Max Raymond Langham and Robert Lowell Davis
Text fields in electronic medical records (EMR) contain information on important factors that influence health outcomes, however, they are underutilized in clinical decision making due to their unstructured nature. We analyzed 6497 inpatient surgical cas...
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