Natural language processing in low back pain and spine diseases: A systematic review

Abstract

Natural Language Processing (NLP) is a discipline at the intersection between Computer Science (CS), Artificial Intelligence (AI), and Linguistics that leverages unstructured human-interpretable (natural) language text. In recent years, it gained momentum also in health-related applications and research. Although preliminary, studies concerning Low Back Pain (LBP) and other related spine disorders with relevant applications of NLP methodologies have been reported in the literature over the last few years. It motivated us to systematically review the literature comprised of two major public databases, PubMed and Scopus. To do so, we first formulated our research question following the PICO guidelines. Then, we followed a PRISMA-like protocol by performing a search query including terminologies of both technical (e.g., natural language and computational linguistics) and clinical (e.g., lumbar and spine surgery) domains. We collected 221 non-duplicated studies, 16 of which were eligible for our analysis. In this work, we present these studies divided into sub-categories, from both tasks and exploited models’ points of view. Furthermore, we report a detailed description of techniques used to extract and process textual features and the several evaluation metrics used to assess the performance of the NLP models. However, what is clear from our analysis is that additional studies on larger datasets are needed to better define the role of NLP in the care of patients with spinal disorders.

Using Natural Language Processing to Identify Low Back Pain in Imaging Reports

“…Dantes et al developed an NLP system based on IDEAL-X to identify venous thromboembolism from electronic medical records [36]. The free-text type clinical note, operation notes, and electronic health records could be used for developing NLP algorithms for identifying or predicting specific spinal diseases or complications of spinal surgery (Table 4) [12].…”

“…Natural language processing (NLP) is defined as understanding, analyzing, and extracting meaningful information from text (natural language) by computer science [12]. NLP, a computer technology specializing in text processing, can be used to extract critical information from unstructured text in electronic health records [13].…”

“…NLP, a computer technology specializing in text processing, can be used to extract critical information from unstructured text in electronic health records [13]. The NLP system is classified into three approaches: the rule-based approach, the machine learning-based approach, and the hybrid types approach [12]. For example, a Bidirectional Encoder Representations from Transformers (BERT)-based NLP pipeline (a state-of-the-art deep learning model for language processing) was used to identify important findings in intensive care chest radiograph reports [14].…”

The use of natural language processing in palliative care research: A scoping review

“…Natural language processing search terms included data mining, text mining, computational linguistics, conversations, medical language processing, corpus analysis, and machine learning. Keywords for natural language processing were adapted from Bacco et al 20 A librarian specialized in biomedical research was consulted to build the full search strategy (Supplemental Appendix 1). All citations were managed through Rayyan and Mendeley software.…”

Threats and opportunities of using ChatGPT in scientific writing—The risk of getting spineless

“…Briefly, ChatGPT is an artificial intelligence (AI)‐based large language model (LLM) platform developed with a technique called Reinforcement Learning from Human Feedback 3 . Basically, the software has been (and is continuously) trained with several text datasets to learn how to generate conversational, human‐like responses, which fall under the Natural Language Processing (NLP) domain of AI 4 . As a result, the user can literally ask whatever question—ranging from simple queries to detailed investigations—and receive an answer in a matter of seconds.…”