AIMC Topic: Natural Language Processing

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Standardizing Heterogeneous Annotation Corpora Using HL7 FHIR for Facilitating their Reuse and Integration in Clinical NLP.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Manually annotated clinical corpora are commonly used as the gold standards for the training and evaluation of clinical natural language processing (NLP) tools. The creation of these manual annotation corpora, however, is both costly and time-consumi...

Clinical Document Classification Using Labeled and Unlabeled Data Across Hospitals.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Reviewing radiology reports in emergency departments is an essential but laborious task. Timely follow-up of patients with abnormal cases in their radiology reports may dramatically affect the patient's outcome, especially if they have been discharge...

Optimizing Corpus Creation for Training Word Embedding in Low Resource Domains: A Case Study in Autism Spectrum Disorder (ASD).

AMIA ... Annual Symposium proceedings. AMIA Symposium
Automating the extraction of behavioral criteria indicative of Autism Spectrum Disorder (ASD) in electronic health records (EHRs) can contribute significantly to the effort to monitor the condition. Word embedding algorithms such as Word2Vec can enco...

Towards the Inference of Social and Behavioral Determinants of Sexual Health: Development of a Gold-Standard Corpus with Semi-Supervised Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Social and behavioral determinants of health (SBDH) are environmental and behavioral factors that are increasingly recognized for their impact on health outcomes. We describe ongoing research to extract SBDH related to sexual health from clinical doc...

An Automated Feature Engineering for Digital Rectal Examination Documentation using Natural Language Processing.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Digital rectal examination (DRE) is considered a quality metric for prostate cancer care. However, much of the DRE related rich information is documented as free-text in clinical narratives. Therefore, we aimed to develop a natural language processin...

Generalized Extraction and Classification of Span-Level Clinical Phrases.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Much of the critical information in a patient's electronic health record (EHR) is hidden in unstructured text. As such, there is an increasing role for automated text extraction and summarization to make this information available in a way that can b...

A Computable Phenotype for Acute Respiratory Distress Syndrome Using Natural Language Processing and Machine Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Acute Respiratory Distress Syndrome (ARDS) is a syndrome of respiratory failure that may be identified using text from radiology reports. The objective of this study was to determine whether natural language processing (NLP) with machine learning per...

Ascertaining Depression Severity by Extracting Patient Health Questionnaire-9 (PHQ-9) Scores from Clinical Notes.

AMIA ... Annual Symposium proceedings. AMIA Symposium
The Patient Health Questionnaire-9 (PHQ-9) is a validated instrument for assessing depression severity. While some electronic health record (EHR) systems capture PHQ-9 scores in a structured format, unstructured clinical notes remain the only source ...

Combination of conditional random field with a rule based method in the extraction of PICO elements.

BMC medical informatics and decision making
BACKGROUND: Extracting primary care information in terms of Patient/Problem, Intervention, Comparison and Outcome, known as PICO elements, is difficult as the volume of medical information expands and the health semantics is complex to capture it fro...

How Cognitive Machines Can Augment Medical Imaging.

AJR. American journal of roentgenology
OBJECTIVE: Artificial intelligence (AI) neural networks rapidly convert disparate facts and data into highly predictive analytic models. Machine learning maps image-patient phenotype correlations opaque to standard statistics. Deep learning performs ...