AIMC Topic: Natural Language Processing

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Natural language processing in text mining for structural modeling of protein complexes.

BMC bioinformatics
BACKGROUND: Structural modeling of protein-protein interactions produces a large number of putative configurations of the protein complexes. Identification of the near-native models among them is a serious challenge. Publicly available results of bio...

Deep neural models for ICD-10 coding of death certificates and autopsy reports in free-text.

Journal of biomedical informatics
We address the assignment of ICD-10 codes for causes of death by analyzing free-text descriptions in death certificates, together with the associated autopsy reports and clinical bulletins, from the Portuguese Ministry of Health. We leverage a deep n...

Efficient Embedded Decoding of Neural Network Language Models in a Machine Translation System.

International journal of neural systems
Neural Network Language Models (NNLMs) are a successful approach to Natural Language Processing tasks, such as Machine Translation. We introduce in this work a Statistical Machine Translation (SMT) system which fully integrates NNLMs in the decoding ...

Development and Validation of a Natural Language Processing Tool to Identify Patients Treated for Pneumonia across VA Emergency Departments.

Applied clinical informatics
BACKGROUND: Identifying pneumonia using diagnosis codes alone may be insufficient for research on clinical decision making. Natural language processing (NLP) may enable the inclusion of cases missed by diagnosis codes.

Evaluating Report Text Variation and Informativeness: Natural Language Processing of CT Chest Imaging for Pulmonary Embolism.

Journal of the American College of Radiology : JACR
OBJECTIVE: The aim of this study was to quantify the variability of language in free text reports of pulmonary embolus (PE) studies and to gauge the informativeness of free text to predict PE diagnosis using machine learning as proxy for human unders...

Automated chart review utilizing natural language processing algorithm for asthma predictive index.

BMC pulmonary medicine
BACKGROUND: Thus far, no algorithms have been developed to automatically extract patients who meet Asthma Predictive Index (API) criteria from the Electronic health records (EHR) yet. Our objective is to develop and validate a natural language proces...

Ascertainment of asthma prognosis using natural language processing from electronic medical records.

The Journal of allergy and clinical immunology
NLP algorithm successfully determined asthma prognosis (i.e., no remission, long-term remission, and intermittent remission) by taking into account asthma symptoms documented in EMR, and addressed the limitations of billing code- based asthma outcome...

Applying natural language processing techniques to develop a task-specific EMR interface for timely stroke thrombolysis: A feasibility study.

International journal of medical informatics
OBJECTIVE: To reduce errors in determining eligibility for intravenous thrombolytic therapy (IVT) in stroke patients through use of an enhanced task-specific electronic medical record (EMR) interface powered by natural language processing (NLP) techn...

Natural Language-based Machine Learning Models for the Annotation of Clinical Radiology Reports.

Radiology
Purpose To compare different methods for generating features from radiology reports and to develop a method to automatically identify findings in these reports. Materials and Methods In this study, 96 303 head computed tomography (CT) reports were ob...

Machine learning to parse breast pathology reports in Chinese.

Breast cancer research and treatment
INTRODUCTION: Large structured databases of pathology findings are valuable in deriving new clinical insights. However, they are labor intensive to create and generally require manual annotation. There has been some work in the bioinformatics communi...