INTRODUCTION: Practice-Based Learning and Improvement, a core competency identified by the Accreditation Council for Graduate Medical Education, carries importance throughout a physician's career. Practice-Based Learning and Improvement is cultivated...
In this op-ed, we discuss the advantages of leveraging natural language processing (NLP) in the assessment of clinical reasoning. Clinical reasoning is a complex competency that cannot be easily assessed using multiple-choice questions. Constructed-r...
Pandemic diseases such as plague have produced a vast amount of literature providing information about the spatiotemporal extent, transmission, or countermeasures. However, the manual extraction of such information from running text is a tedious proc...
OBJECTIVE: Tracking global health funding is a crucial but time consuming and labor-intensive process. This study aimed to develop a framework to automate the tracking of global health spending using natural language processing (NLP) and machine lear...
BACKGROUND: Decisions in healthcare usually rely on the goodness and completeness of data that could be coupled with heuristics to improve the decision process itself. However, this is often an incomplete process. Structured interviews denominated De...
BACKGROUND: Unstructured text in medical records, such as Electronic Health Records, contain an enormous amount of valuable information for research; however, it is difficult to extract and structure important information because of frequent typograp...
OBJECTIVE: Biomedical named entity normalization (BNEN) is a fundamental natural language processing (NLP) task in the biomedical domain. Many representation learning-based methods have been successfully applied to BNEN in recent years. Most of them ...
Pre-trained natural language processing models on a large natural language corpus can naturally transfer learned knowledge to protein domains by fine-tuning specific in-domain tasks. However, few studies focused on enriching such protein language mod...
The steady rise of online shopping goes hand in hand with the development of increasingly complex ML and NLP models. While most use cases are cast as specialized supervised learning problems, we argue that practitioners would greatly benefit from gen...
There are currently >1.3 million human -omics samples that are publicly available. This valuable resource remains acutely underused because discovering particular samples from this ever-growing data collection remains a significant challenge. The maj...
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