AIMC Topic: Machine Learning

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CoRTEx: contrastive learning for representing terms via explanations with applications on constructing biomedical knowledge graphs.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Biomedical Knowledge Graphs play a pivotal role in various biomedical research domains. Concurrently, term clustering emerges as a crucial step in constructing these knowledge graphs, aiming to identify synonymous terms. Due to a lack of ...

Generative large language models are all-purpose text analytics engines: text-to-text learning is all your need.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To solve major clinical natural language processing (NLP) tasks using a unified text-to-text learning architecture based on a generative large language model (LLM) via prompt tuning.

Unsupervised Denoising and Super-Resolution of Vascular Flow Data by Physics-Informed Machine Learning.

Journal of biomechanical engineering
We present an unsupervised deep learning method to perform flow denoising and super-resolution without high-resolution labels. We demonstrate the ability of a single model to reconstruct three-dimensional stenosis and aneurysm flows, with varying geo...

Ensemble pretrained language models to extract biomedical knowledge from literature.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: The rapid expansion of biomedical literature necessitates automated techniques to discern relationships between biomedical concepts from extensive free text. Such techniques facilitate the development of detailed knowledge bases and highl...

Clinical risk prediction using language models: benefits and considerations.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The use of electronic health records (EHRs) for clinical risk prediction is on the rise. However, in many practical settings, the limited availability of task-specific EHR data can restrict the application of standard machine learning pipe...

Studying Privacy Aspects of Learned Knowledge Bases in the Context of Synthetic and Medical Data.

Studies in health technology and informatics
INTRODUCTION: Retrieving comprehensible rule-based knowledge from medical data by machine learning is a beneficial task, e.g., for automating the process of creating a decision support system. While this has recently been studied by means of exceptio...

On-site analysis and rapid identification of citrus herbs by miniature mass spectrometry and machine learning.

Rapid communications in mass spectrometry : RCM
BACKGROUND: Natural medicines present a considerable analytical challenge due to their diverse botanical origins and complex multi-species composition. This inherent complexity complicates their rapid identification and analysis. Tangerine peel, a pr...