Modern large language models generate texts that are virtually indistinguishable from those written by humans and achieve near-human performance in comprehension and reasoning tests. Yet, their complexity makes it difficult to explain and predict the...
International journal of radiation oncology, biology, physics
Mar 27, 2023
PURPOSE: Real-world evidence for radiation therapy (RT) is limited because it is often documented only in the clinical narrative. We developed a natural language processing system for automated extraction of detailed RT events from text to support cl...
International journal of language & communication disorders
Mar 24, 2023
BACKGROUND: In the past few years there has been a growing interest in the employment of verbal productions as digital biomarkers, namely objective, quantifiable behavioural data that can be collected and measured by means of digital devices, allowin...
Randomized controlled trials (RCTs) play a major role in aiding biomedical research and practices. To inform this research, the demand for highly accurate retrieval of scientific articles on RCT research has grown in recent decades. However, correctl...
The analysis of omic data depends on machine-readable information about protein interactions, modifications, and activities as found in protein interaction networks, databases of post-translational modifications, and curated models of gene and protei...
The citation network of patents citing prior art arises from the legal obligation of patent applicants to properly disclose their invention. One way to study the relationship between current patents and their antecedents is by analyzing the similarit...
Natural language processing (NLP) is an area of artificial intelligence that applies information technologies to process the human language, understand it to a certain degree, and use it in various applications. This area has rapidly developed in the...
BACKGROUND: Rapidly and efficiently identifying critically ill infants for whole genome sequencing (WGS) is a costly and challenging task currently performed by scarce, highly trained experts and is a major bottleneck for application of WGS in the NI...
BACKGROUND AND OBJECTIVE: Diagnostic uncertainty, when unrecognized or poorly communicated, can result in diagnostic error. However, diagnostic uncertainty is challenging to study due to a lack of validated identification methods. This study aims to ...
BACKGROUND: A huge amount of clinical data is generated daily and it is usually filed in clinical reports as natural language. Data extraction and further analysis requires reading and manual review of each report, which is a time consuming process. ...
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