AIMC Topic: Medical Informatics

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Speculation detection for Chinese clinical notes: Impacts of word segmentation and embedding models.

Journal of biomedical informatics
Speculations represent uncertainty toward certain facts. In clinical texts, identifying speculations is a critical step of natural language processing (NLP). While it is a nontrivial task in many languages, detecting speculations in Chinese clinical ...

Natural Language Processing for Cohort Discovery in a Discharge Prediction Model for the Neonatal ICU.

Applied clinical informatics
OBJECTIVES: Discharging patients from the Neonatal Intensive Care Unit (NICU) can be delayed for non-medical reasons including the procurement of home medical equipment, parental education, and the need for children's services. We previously created ...

A Q-backpropagated time delay neural network for diagnosing severity of gait disturbances in Parkinson's disease.

Journal of biomedical informatics
Parkinson's disease (PD) is a movement disorder that affects the patient's nervous system and health-care applications mostly uses wearable sensors to collect these data. Since these sensors generate time stamped data, analyzing gait disturbances in ...

Reverse Engineering and Evaluation of Prediction Models for Progression to Type 2 Diabetes: An Application of Machine Learning Using Electronic Health Records.

Journal of diabetes science and technology
BACKGROUND: Application of novel machine learning approaches to electronic health record (EHR) data could provide valuable insights into disease processes. We utilized this approach to build predictive models for progression to prediabetes and type 2...

An unsupervised learning method to identify reference intervals from a clinical database.

Journal of biomedical informatics
Reference intervals are critical for the interpretation of laboratory results. The development of reference intervals using traditional methods is time consuming and costly. An alternative approach, known as an a posteriori method, requires an expert...

User-defined functions in the Arden Syntax: An extension proposal.

Artificial intelligence in medicine
BACKGROUND: The Arden Syntax is a knowledge-encoding standard, started in 1989, and now in its 10th revision, maintained by the health level seven (HL7) organization. It has constructs borrowed from several language concepts that were available at th...

Stabilizing l1-norm prediction models by supervised feature grouping.

Journal of biomedical informatics
Emerging Electronic Medical Records (EMRs) have reformed the modern healthcare. These records have great potential to be used for building clinical prediction models. However, a problem in using them is their high dimensionality. Since a lot of infor...

Clinical decision support systems at the Vienna General Hospital using Arden Syntax: Design, implementation, and integration.

Artificial intelligence in medicine
INTRODUCTION: The Allgemeines Krankenhaus Informations Management (AKIM) project was started at the Vienna General Hospital (VGH) several years ago. This led to the introduction of a new hospital information system (HIS), and the installation of the ...

Data-driven knowledge acquisition, validation, and transformation into HL7 Arden Syntax.

Artificial intelligence in medicine
OBJECTIVE: The objective of this study is to help a team of physicians and knowledge engineers acquire clinical knowledge from existing practices datasets for treatment of head and neck cancer, to validate the knowledge against published guidelines, ...

Assessing the feasibility of a mobile health-supported clinical decision support system for nutritional triage in oncology outpatients using Arden Syntax.

Artificial intelligence in medicine
BACKGROUND: Nutritional screening procedures followed by regular nutrition monitoring for oncological outpatients are no standard practice in many European hospital wards and outpatient settings. As a result, early signs of malnutrition are missed an...