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Electronic Health Records

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Clinical and research applications of natural language processing for heart failure.

Heart failure reviews
Natural language processing (NLP) is a burgeoning field of machine learning/artificial intelligence that focuses on the computational processing of human language. Researchers and clinicians are using NLP methods to advance the field of medicine in g...

Detecting cardiovascular diseases using unsupervised machine learning clustering based on electronic medical records.

BMC medical research methodology
BACKGROUND: Electronic medical records (EMR)-trained machine learning models have the potential in CVD risk prediction by integrating a range of medical data from patients, facilitate timely diagnosis and classification of CVDs. We tested the hypothe...

Data-Driven Decision Support Tool Co-Development with a Primary Health Care Practice Based Learning Network.

F1000Research
BACKGROUND: The Alliance for Healthier Communities is a learning health system that supports Community Health Centres (CHCs) across Ontario, Canada to provide team-based primary health care to people who otherwise experience barriers to care. This ca...

OptimCLM: Optimizing clinical language models for predicting patient outcomes via knowledge distillation, pruning and quantization.

International journal of medical informatics
BACKGROUND: Clinical Language Models (CLMs) possess the potential to reform traditional healthcare systems by aiding in clinical decision making and optimal resource utilization. They can enhance patient outcomes and help healthcare management throug...

Large language models can accurately populate Vascular Quality Initiative procedural databases using narrative operative reports.

Journal of vascular surgery
OBJECTIVE: Participation in the Vascular Quality Initiative (VQI) provides important resources to surgeons, but the ability to do so is often limited by time and data entry personnel. Large language models (LLMs) such as ChatGPT (OpenAI) are examples...

Engineering of Generative Artificial Intelligence and Natural Language Processing Models to Accurately Identify Arrhythmia Recurrence.

Circulation. Arrhythmia and electrophysiology
BACKGROUND: Large language models (LLMs) such as Chat Generative Pre-trained Transformer (ChatGPT) excel at interpreting unstructured data from public sources, yet are limited when responding to queries on private repositories, such as electronic hea...

Investigating Older Adults' Perceptions of AI Tools for Medication Decisions: Vignette-Based Experimental Survey.

Journal of medical Internet research
BACKGROUND: Given the public release of large language models, research is needed to explore whether older adults would be receptive to personalized medication advice given by artificial intelligence (AI) tools.

Active learning for extracting rare adverse events from electronic health records: A study in pediatric cardiology.

International journal of medical informatics
OBJECTIVE: Automate the extraction of adverse events from the text of electronic medical records of patients hospitalized for cardiac catheterization.

Assessing Large Language Models for Oncology Data Inference From Radiology Reports.

JCO clinical cancer informatics
PURPOSE: We examined the effectiveness of proprietary and open large language models (LLMs) in detecting disease presence, location, and treatment response in pancreatic cancer from radiology reports.

Enhancing Thyroid Pathology With Artificial Intelligence: Automated Data Extraction From Electronic Health Reports Using RUBY.

JCO clinical cancer informatics
PURPOSE: Thyroid nodules are common in the general population, and assessing their malignancy risk is the initial step in care. Surgical exploration remains the sole definitive option for indeterminate nodules. Extensive database access is crucial fo...