Medical & biological engineering & computing
Nov 1, 2024
Accurate recognition and linking of oncologic entities in clinical notes is essential for extracting insights across cancer research, patient care, clinical decision-making, and treatment optimization. We present the Neuro-Symbolic System for Cancer ...
BACKGROUND: Title-abstract screening in the preparation of a systematic review is a time-consuming task. Modern techniques of natural language processing and machine learning might allow partly automatization of title-abstract screening. In particula...
PURPOSE: Medical reports, governed by HIPAA regulations, contain personal health information (PHI), restricting secondary data use. Utilizing natural language processing (NLP) and large language models (LLM), we sought to employ publicly available me...
BACKGROUND: ChatGPT, a large language model artificial intelligence platform that uses natural language processing, has seen its implementation across a number of sectors, notably in health care. However, there remains limited understanding regarding...
Pre-trained Large Language Models (LLMs) have revolutionised Natural Language Processing (NLP) tasks, but often struggle when applied to specialised domains such as healthcare. The traditional approach of pre-training on large datasets followed by ta...
IEEE transactions on neural networks and learning systems
Oct 29, 2024
When the first transformer-based language models were published in the late 2010s, pretraining with general text and then fine-tuning the model on a task-specific dataset often achieved the state-of-the-art performance. However, more recent work sugg...
IEEE transactions on neural networks and learning systems
Oct 29, 2024
Word representations, usually derived from a large corpus and endowed with rich semantic information, have been widely applied to natural language tasks. Traditional deep language models, on the basis of dense word representations, requires large mem...
Journal of the American Heart Association
Oct 25, 2024
BACKGROUND: Multicenter electronic health records can support quality improvement and comparative effectiveness research in stroke. However, limitations of electronic health record-based research include challenges in abstracting key clinical variabl...
OBJECTIVE: Although deep learning techniques have shown significant achievements, they frequently depend on extensive amounts of hand-labeled data and tend to perform inadequately in few-shot scenarios. The objective of this study is to devise a stra...
INTRODUCTION: Peripheral arterial disease (PAD) is the leading cause of amputation in the United States. Despite affecting 8.5 million Americans and more than 200 million people globally, there are significant gaps in awareness by both patients and p...