AIMC Topic: Electronic Health Records

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Consolidated EHR Workflow for Endoscopy Quality Reporting.

Studies in health technology and informatics
Although colonoscopy is the most frequently performed endoscopic procedure, the lack of standardized reporting is impeding clinical and translational research. Inadequacies in data extraction from the raw, unstructured text in electronic health recor...

A Deep Learning Framework for Automated ICD-10 Coding.

Studies in health technology and informatics
The International Statistical Classification of Diseases and Related Health Problems (ICD) is one of the widely used classification system for diagnoses and procedures to assign diagnosis codes to Electronic Health Record (EHR) associated with a pati...

Inter-Rater Reliability of Unstructured Text Labeling: Artificially vs. Naturally Intelligent Approaches.

Studies in health technology and informatics
Unstructured medical text labeling technologies are expected to be highly demanded since the interest in artificial intelligence and natural language processing arises in the medical domain. Our study aimed to assess the agreement between experts who...

Machine Learning Based Risk Prediction for Major Adverse Cardiovascular Events.

Studies in health technology and informatics
BACKGROUND: Patients with major adverse cardiovascular events (MACE) such as myocardial infarction or stroke suffer from frequent hospitalizations and have high mortality rates. By identifying patients at risk at an early stage, MACE can be prevented...

Automated Identification of Patients With Immune-Related Adverse Events From Clinical Notes Using Word Embedding and Machine Learning.

JCO clinical cancer informatics
PURPOSE: Although immune checkpoint inhibitors (ICIs) have substantially improved survival in patients with advanced malignancies, they are associated with a unique spectrum of side effects termed immune-related adverse events (irAEs). To ensure trea...

Automated NLP Extraction of Clinical Rationale for Treatment Discontinuation in Breast Cancer.

JCO clinical cancer informatics
PURPOSE: Key oncology end points are not routinely encoded into electronic medical records (EMRs). We assessed whether natural language processing (NLP) can abstract treatment discontinuation rationale from unstructured EMR notes to estimate toxicity...

Natural Language Processing in Surgery: A Systematic Review and Meta-analysis.

Annals of surgery
OBJECTIVE: The aim of this study was to systematically assess the application and potential benefits of natural language processing (NLP) in surgical outcomes research.

Natural Language Processing to Identify Cancer Treatments With Electronic Medical Records.

JCO clinical cancer informatics
PURPOSE: Knowing the treatments administered to patients with cancer is important for treatment planning and correlating treatment patterns with outcomes for personalized medicine study. However, existing methods to identify treatments are often lack...

Deep learning in systems medicine.

Briefings in bioinformatics
Systems medicine (SM) has emerged as a powerful tool for studying the human body at the systems level with the aim of improving our understanding, prevention and treatment of complex diseases. Being able to automatically extract relevant features nee...

Deep learning for biological age estimation.

Briefings in bioinformatics
Modern machine learning techniques (such as deep learning) offer immense opportunities in the field of human biological aging research. Aging is a complex process, experienced by all living organisms. While traditional machine learning and data minin...