The xCures platform aggregates, organizes, structures, and normalizes clinical EMR data across care sites, utilizing advanced technologies for near real-time access. The platform generates data in a format to support clinical care, accelerate researc...
Various decisions concerning the management, display, and diagnostic use of electronic health records (EHR) data can be automated using machine learning (ML). We describe how ML is currently applied to EHR data and how it may be applied in the near f...
AIM: The aim of the article is to analyze the current state of functioning of the medical information space of Ukraine in order to formulate scientifically sound proposals aimed at improving the implementation of medical reform.
PURPOSE: The RECIST guidelines provide a standardized approach for evaluating the response of cancer to treatment, allowing for consistent comparison of treatment efficacy across different therapies and patients. However, collecting such information ...
BACKGROUND: Children presenting to primary care with suspected type 1 diabetes should be referred immediately to secondary care to avoid life-threatening diabetic ketoacidosis. However, early recognition of children with type 1 diabetes is challengin...
Studies in health technology and informatics
May 23, 2024
This paper explores the potential of leveraging electronic health records (EHRs) for personalized health research through the application of artificial intelligence (AI) techniques, specifically Named Entity Recognition (NER). By extracting crucial p...
Studies in health technology and informatics
May 23, 2024
Inconsistent disease coding standards in medicine create hurdles in data exchange and analysis. This paper proposes a machine learning system to address this challenge. The system automatically matches unstructured medical text (doctor notes, complai...
Journal of the American Medical Informatics Association : JAMIA
May 20, 2024
OBJECTIVE: Machine learning (ML) is increasingly employed to diagnose medical conditions, with algorithms trained to assign a single label using a black-box approach. We created an ML approach using deep learning that generates outcomes that are tran...
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