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Journal of Biomedical Informatics
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2.95
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2732
Papers 2753
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Abstract Background The use of machine learning techniques is especially pertinent to the composite and challenging conditions of emergency departments (EDs). Repeat ED visits (i.e. revisits) are an example of potentially inappropriate utilization of resources that can be forecasted by these techniques. Objective To track the ED revisit risk over time using the hidden Markov model (HMM) as a major latent class model. Given the HMM states, we carried out forecasting of future ED revisits with var...
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Abstract The fast development of today’s healthcare and the need to extract new medical knowledge from exponentially-growing volumes of standardized Electronic Health Records data, as required by studies in Precision Medicine, brings up a challenge that may probably only be addressed using NoSQL DBMSs, due to the non-optimal performance of traditional relational DBMSs on standardized data; and these database systems operated by semantic archetype-based query languages, because of the expected ge...
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Abstract Heart Failure (HF) is one of the most common causes of hospitalization and is burdened by short-term (in-hospital) and long-term (6 to 12 month) mortality. Accurate prediction of HF mortality plays a critical role in evaluating early treatment effects. However, due to the lack of a simple and effective prediction model, mortality prediction of HF is difficult, resulting in a low rate of control. To handle this issue, we propose a Weight-based Multiple Empirical Kernel Learning with Neig...
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Abstract Objective Sensitive health information possesses risks, such as stigma and discrimination, when disclosed. Few studies have used a patient’s own electronic health records (EHRs) to explore what types of information are considered sensitive and how such perceptions affect data sharing preferences. After a systematic literature review, we designed and piloted a mixed-method approach that employs an individual’s own records to assess content sensitivity and preferences for granular data sh...
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#1Ioakeim Perros (Sutter Health)H-Index: 6
#2Xiaowei Yan (Sutter Health)H-Index: 2
Last.Walter F. StewartH-Index: 97
view all 5 authors...
Abstract Background Activity or audit log data are required for EHR privacy and security management but may also be useful for understanding desktop workflow. Objective We determined if the EHR audit log file, a rich source of complex time-stamped data on desktop activities, could be processed to derive primary care provider (PCP) level workflow measures. Methods We analyzed audit log data on 876 PCPs across 17,455 ambulatory care encounters that generated 578,394 time-stamped records. Each indi...
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Abstract Despite being able to make accurate predictions, most existing prognostic models lack a proper indication about the uncertainty of each prediction, that is, the risk of prediction error for individual patients. This hampers their translation to primary care settings through decision support systems. To address this problem, we studied different methods for transforming classifiers into probabilistic/confidence-based predictors (here called uncertainty methods), where predictions are com...
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Abstract Voice technology has grown tremendously in recent years and using voice as a biomarker has also been gaining evidence. We demonstrate the potential of voice in serving as a deep phenotype for Parkinson’s Disease (PD), the second most common neurodegenerative disorder worldwide, by presenting methodology for voice signal processing for clinical analysis. Detection of PD symptoms typically requires an exam by a movement disorder specialist and can be hard to access and inconsistent in fin...
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Machine learning
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