AIMC Topic: Medical Records Systems, Computerized

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An efficient prototype method to identify and correct misspellings in clinical text.

BMC research notes
OBJECTIVE: Misspellings in clinical free text present challenges to natural language processing. With an objective to identify misspellings and their corrections, we developed a prototype spelling analysis method that implements Word2Vec, Levenshtein...

Using Machine Learning to Predict the Information Seeking Behavior of Clinicians Using an Electronic Medical Record System.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Poor electronic medical record (EMR) usability is detrimental to both clinicians and patients. A better EMR would provide concise, context sensitive patient data, but doing so entails the difficult task of knowing which data are relevant. To determin...

Mining Electronic Health Records to Extract Patient-Centered Outcomes Following Prostate Cancer Treatment.

AMIA ... Annual Symposium proceedings. AMIA Symposium
The clinical, granular data in electronic health record (EHR) systems provide opportunities to improve patient care using informatics retrieval methods. However, it is well known that many methodological obstacles exist in accessing data within EHRs....

Open Globe Injury Patient Identification in Warfare Clinical Notes.

AMIA ... Annual Symposium proceedings. AMIA Symposium
The aim of this study is to utilize the Defense and Veterans Eye Injury and Vision Registry clinical data derived from DoD and VA medical systems which include documentation of care while in combat, and develop methods for comprehensive and reliable ...

Healthcare Text Classification System and its Performance Evaluation: A Source of Better Intelligence by Characterizing Healthcare Text.

Journal of medical systems
A machine learning (ML)-based text classification system has several classifiers. The performance evaluation (PE) of the ML system is typically driven by the training data size and the partition protocols used. Such systems lead to low accuracy becau...

Complex analyses on clinical information systems using restricted natural language querying to resolve time-event dependencies.

Journal of biomedical informatics
PURPOSE: This paper reports on a generic framework to provide clinicians with the ability to conduct complex analyses on elaborate research topics using cascaded queries to resolve internal time-event dependencies in the research questions, as an ext...

A New Data Representation Based on Training Data Characteristics to Extract Drug Name Entity in Medical Text.

Computational intelligence and neuroscience
One essential task in information extraction from the medical corpus is drug name recognition. Compared with text sources come from other domains, the medical text mining poses more challenges, for example, more unstructured text, the fast growing of...

Detection of sentence boundaries and abbreviations in clinical narratives.

BMC medical informatics and decision making
BACKGROUND: In Western languages the period character is highly ambiguous, due to its double role as sentence delimiter and abbreviation marker. This is particularly relevant in clinical free-texts characterized by numerous anomalies in spelling, pun...

An electronic medical record system with treatment recommendations based on patient similarity.

Journal of medical systems
As the core of health information technology (HIT), electronic medical record (EMR) systems have been changing to meet health care demands. To construct a new-generation EMR system framework with the capability of self-learning and real-time feedback...

An eligibility criteria query language for heterogeneous data warehouses.

Methods of information in medicine
INTRODUCTION: This article is part of the Focus Theme of METHODS of Information in Medicine on "Managing Interoperability and Complexity in Health Systems".