Academic Articles & Research Papers

Thyroid Ultrasound Appropriateness Identification Through Natural Language Processing of Electronic Health Records

Objective: To address thyroid cancer overdiagnosis, we aim to develop a natural language processing (NLP) algorithm to determine the appropriateness of thyroid ultrasounds (TUS). Patients and Methods: Between 2017 and 2021, we identified 18...

Natural Language Processing for EHR-Based Computational Phenotyping

This article reviews recent advances in applying natural language processing (NLP) to Electronic Health Records (EHRs) for computational phenotyping. NLP-based computational phenotyping has numerous applications including diagnosis categori...

A Review of Natural Language Processing in Medical Education

Natural language processing (NLP) aims to program machines to interpret human language as humans do. It could quantify aspects of medical education that were previously amenable only to qualitative methods. The application of NLP to medical...

Natural Language Processing Applications in Business

Increasing dependency of humans on computer-assisted systems has led to researchers focusing on more effective communication technologies that can mimic human interactions as well as understand natural languages and human emotions. The prob...

Natural Language Processing

Researchers in natural language processing (NLP) apply computational techniques to the understanding and generation of human language. Currently, we are focusing on the development of grammatical formalisms and parsing algorithms, appropria...

The Stanford CoreNLP Natural Language Processing Toolkit

Christopher Manning, Mihai Surdeanu, John Bauer, Jenny Finkel, Steven Bethard, David McClosky. Proceedings of 52nd Annual Meeting of the Association for Computational Linguistics: System Demonstrations. 2014....

Natural Language Processing for Information Retrieval

Natural language processing (NLP) is the computerized approach to analyzing text that is based on both a set of theories and a set of technologies. Although NLP is a relatively recent area of research and application, compared with other in...

Natural Language Processing

The primary concern of natural language processing is the design and implementation of computational systems for analysing and understanding human languages to automate certain real-life tasks demanding human language abilities. It is typic...

Natural Language Processing of Social Media as Screening for Suicide Risk

Suicide is among the 10 most common causes of death, as assessed by the World Health Organization. For every death by suicide, an estimated 138 people's lives are meaningfully affected, and almost any other statistic around suicide deaths i...

Evaluation of natural language processors

Despite a large amount of research on developing natural language understanding programs, little work has been done on evaluating their performance or potential. The evaluations that have been done have been unsystematic and incomplete. Thi...

Nanomaterial-based therapeutic strategies for systemic autoimmune rheumatic diseases: from molecular mechanisms to preclinical translation.

Evidence gaps and route-dependent development requirements for CAR cellular therapy in urothelial carcinoma: a systematic evidence map and public-data analysis.

NeuroBlu, an electronic health record (EHR) trusted research environment (TRE) to support mental healthcare analytics with real-world data

Purpose NeuroBlu is a real-world data (RWD) repository that contains deidentified electronic health record (EHR) data from US mental healthcare providers operating the MindLinc EHR system. NeuroBlu enables users to perform statistical analy...

Empowering text classification with NLP and explainable AI for enhanced interpretability

Abstract Artificial intelligence (AI) models have demonstrated significant success in classifying various types of text. However, the complex nature of these models often complicates the interpretability of their classifications. To address...

Using 311 data to develop an algorithm to identify urban blight for public health improvement.

The growth of administrative data made available publicly, often in near-real time, offers new opportunities for monitoring conditions that impact community health. Urban blight-manifestations of adverse social processes in the urban enviro...

Comparative Study of CNN and RNN for Natural Language Processing

Deep neural networks (DNN) have revolutionized the field of natural language processing (NLP). Convolutional neural network (CNN) and recurrent neural network (RNN), the two main types of DNN architectures, are widely explored to handle var...

"Hard-To-Reach" Voices: Methodology of Qualitative Research on Violence Against Women With Disabilities-A Systematic Review.

Methods for Analyzing the Contents of Social Media for Health Care: Scoping Review

BackgroundGiven the rapid development of social media, effective extraction and analysis of the contents of social media for health care have attracted widespread attention from health care providers. As far as we know, most of the reviews ...

One Picture and One Thousand Words: Toward integrated multimodal generative models

Thanks to independent advances in language and image generation, we could soon be in the position to have systems that communicate with us by combining language and images in their output, a skill that humans do not possess (we receive, but...

Enhancing educational semantic retrieval through dual objective fine tuning of open source embedding models

Abstract Recent advances in AI have catalyzed the adoption of intelligent educational tools, yet many semantic retrieval systems remain ill-suited to the unique linguistic and structural characteristics of academic content. This study prese...