AIMC Topic: Electronic Health Records
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Preserving privacy in big data research: the role of federated learning in spine surgery.
European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
Feb 25, 2024
PURPOSE: Integrating machine learning models into electronic medical record systems can greatly enhance decision-making, patient outcomes, and value-based care in healthcare systems. Challenges related to data accessibility, privacy, and sharing can ...
Large language models for science and medicine.
European journal of clinical investigation
Feb 21, 2024
Large language models (LLMs) are a type of machine learning model that learn statistical patterns over text, such as predicting the next words in a sequence of text. Both general purpose and task-specific LLMs have demonstrated potential across diver...
AssistMED project: Transforming cardiology cohort characterisation from electronic health records through natural language processing - Algorithm design, preliminary results, and field prospects.
International journal of medical informatics
Feb 19, 2024
INTRODUCTION: Electronic health records (EHR) are of great value for clinical research. However, EHR consists primarily of unstructured text which must be analysed by a human and coded into a database before data analysis- a time-consuming and costly...
Automatic de-identification of French electronic health records: a cost-effective approach exploiting distant supervision and deep learning models.
BMC medical informatics and decision making
Feb 16, 2024
BACKGROUND: Electronic health records (EHRs) contain valuable information for clinical research; however, the sensitive nature of healthcare data presents security and confidentiality challenges. De-identification is therefore essential to protect pe...
Bolstering Advance Care Planning Measurement Using Natural Language Processing.
Journal of palliative medicine
Feb 6, 2024
Despite its growth as a clinical activity and research topic, the complex dynamic nature of advance care planning (ACP) has posed serious challenges for researchers hoping to quantitatively measure it. Methods for measurement have traditionally depen...
Extracting adverse drug events from clinical Notes: A systematic review of approaches used.
Journal of biomedical informatics
Feb 6, 2024
BACKGROUND: An adverse drug event (ADE) is any unfavorable effect that occurs due to the use of a drug. Extracting ADEs from unstructured clinical notes is essential to biomedical text extraction research because it helps with pharmacovigilance and p...
SPeC: A Soft Prompt-Based Calibration on Performance Variability of Large Language Model in Clinical Notes Summarization.
Journal of biomedical informatics
Feb 5, 2024
Electronic health records (EHRs) store an extensive array of patient information, encompassing medical histories, diagnoses, treatments, and test outcomes. These records are crucial for enabling healthcare providers to make well-informed decisions re...
Natural language processing for electronic health records in anaesthesiology: an introduction to clinicians with recommendations and pitfalls.
Journal of clinical monitoring and computing
Feb 4, 2024
Potential merits and flaws of large language models in epilepsy care: A critical review.
Epilepsia
Feb 2, 2024
The current pace of development and applications of large language models (LLMs) is unprecedented and will impact future medical care significantly. In this critical review, we provide the background to better understand these novel artificial intell...
Using Natural Language Processing to Identify Different Lens Pathology in Electronic Health Records.
American journal of ophthalmology
Feb 1, 2024
PURPOSE: Nearly all published ophthalmology-related Big Data studies rely exclusively on International Classification of Diseases (ICD) billing codes to identify patients with particular ocular conditions. However, inaccurate or nonspecific codes may...
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