AIMC Topic: Electronic Health Records

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Deep Patient Similarity Learning for Personalized Healthcare.

IEEE transactions on nanobioscience
Predicting patients' risk of developing certain diseases is an important research topic in healthcare. Accurately identifying and ranking the similarity among patients based on their historical records is a key step in personalized healthcare. The el...

Simulation of patient flow in multiple healthcare units using process and data mining techniques for model identification.

Journal of biomedical informatics
INTRODUCTION: An approach to building a hybrid simulation of patient flow is introduced with a combination of data-driven methods for automation of model identification. The approach is described with a conceptual framework and basic methods for comb...

Evaluating the Efficiency and Safety of Speech Recognition within a Commercial Electronic Health Record System: A Replication Study.

Applied clinical informatics
OBJECTIVE: To conduct a replication study to validate previously identified significant risks and inefficiencies associated with the use of speech recognition (SR) for documentation within an electronic health record (EHR) system.

Querying archetype-based EHRs by search ontology-based XPath engineering.

Journal of biomedical semantics
BACKGROUND: Legacy data and new structured data can be stored in a standardized format as XML-based EHRs on XML databases. Querying documents on these databases is crucial for answering research questions. Instead of using free text searches, that le...

Imaging, Health Record, and Artificial Intelligence: Hype or Hope?

Current cardiology reports
PURPOSE OF REVIEW: The review is focused on "digital health", which means advanced analytics based on multi-modal data. The "Health Care Internet of Things", which uses sensors, apps, and remote monitoring could provide continuous clinical informatio...

Using machine learning to identify patterns of lifetime health problems in decedents with autism spectrum disorder.

Autism research : official journal of the International Society for Autism Research
Very little is known about the health problems experienced by individuals with autism spectrum disorder (ASD) throughout their life course. We retrospectively analyzed diagnostic codes associated with de-identified electronic health records using a m...

Deep generative learning for automated EHR diagnosis of traditional Chinese medicine.

Computer methods and programs in biomedicine
BACKGROUND: Computer-aided medical decision-making (CAMDM) is the method to utilize massive EMR data as both empirical and evidence support for the decision procedure of healthcare activities. Well-developed information infrastructure, such as hospit...

Natural Language Processing Accurately Calculates Adenoma and Sessile Serrated Polyp Detection Rates.

Digestive diseases and sciences
BACKGROUND: ADR is a widely used colonoscopy quality indicator. Calculation of ADR is labor-intensive and cumbersome using current electronic medical databases. Natural language processing (NLP) is a method used to extract meaning from unstructured o...

EMR-based medical knowledge representation and inference via Markov random fields and distributed representation learning.

Artificial intelligence in medicine
OBJECTIVE: Electronic medical records (EMRs) contain medical knowledge that can be used for clinical decision support (CDS). Our objective is to develop a general system that can extract and represent knowledge contained in EMRs to support three CDS ...

DDC-Outlier: Preventing Medication Errors Using Unsupervised Learning.

IEEE journal of biomedical and health informatics
Electronic health records have brought valuable improvements to hospital practices by integrating patient information. In fact, the understanding of these data can prevent mistakes that may put patients' lives at risk. Nonetheless, to the best of our...