A scoping review of large language model based approaches for information extraction from radiology reports
Radiological imaging is a globally prevalent diagnostic method, yet the free text contained in
radiology reports is not frequently used for secondary purposes. Natural Language …
radiology reports is not frequently used for secondary purposes. Natural Language …
From intuition to AI: evolution of small molecule representations in drug discovery
Within drug discovery, the goal of AI scientists and cheminformaticians is to help identify
molecular starting points that will develop into safe and efficacious drugs while reducing …
molecular starting points that will develop into safe and efficacious drugs while reducing …
Evaluating the performance of Generative Pre-trained Transformer-4 (GPT-4) in standardizing radiology reports
Objective Radiology reporting is an essential component of clinical diagnosis and decision-
making. With the advent of advanced artificial intelligence (AI) models like GPT-4 …
making. With the advent of advanced artificial intelligence (AI) models like GPT-4 …
Feasibility of using the privacy-preserving large language model Vicuna for labeling radiology reports
Background Large language models (LLMs) such as ChatGPT, though proficient in many
text-based tasks, are not suitable for use with radiology reports due to patient privacy …
text-based tasks, are not suitable for use with radiology reports due to patient privacy …
Understanding and mitigating bias in imaging artificial intelligence
Artificial intelligence (AI) algorithms are prone to bias at multiple stages of model
development, with potential for exacerbating health disparities. However, bias in imaging AI …
development, with potential for exacerbating health disparities. However, bias in imaging AI …
Natural language processing to predict isocitrate dehydrogenase genotype in diffuse glioma using MR radiology reports
Objectives To evaluate the performance of natural language processing (NLP) models to
predict isocitrate dehydrogenase (IDH) mutation status in diffuse glioma using routine MR …
predict isocitrate dehydrogenase (IDH) mutation status in diffuse glioma using routine MR …
Domain-adapted large language models for classifying nuclear medicine reports
Purpose To evaluate the impact of domain adaptation on the performance of language
models in predicting five-point Deauville scores on the basis of clinical fluorine 18 …
models in predicting five-point Deauville scores on the basis of clinical fluorine 18 …
A study of deep active learning methods to reduce labelling efforts in biomedical relation extraction
Automatic biomedical relation extraction (bioRE) is an essential task in biomedical research
in order to generate high-quality labelled data that can be used for the development of …
in order to generate high-quality labelled data that can be used for the development of …
Deep-Transfer-Learning–Based Natural Language Processing of Serial Free-Text Computed Tomography Reports for Predicting Survival of Patients With Pancreatic …
S Kim, S Kim, E Kim, M Cecchini, MS Park… - JCO Clinical Cancer …, 2024 - ascopubs.org
PURPOSE To explore the predictive potential of serial computed tomography (CT) radiology
reports for pancreatic cancer survival using natural language processing (NLP). METHODS …
reports for pancreatic cancer survival using natural language processing (NLP). METHODS …
Towards automated transcribing and coding of embodied teamwork communication through multimodal learning analytics
Effective collaboration and teamwork skills are critical in high‐risk sectors, as deficiencies in
these areas can result in injuries and risk of death. To foster the growth of these vital skills …
these areas can result in injuries and risk of death. To foster the growth of these vital skills …