Academic Articles & Research Papers

Natural Language Processing of Clinical Notes on Chronic Diseases: Systematic Review

BACKGROUND: Novel approaches that complement and go beyond evidence-based medicine are required in the domain of chronic diseases, given the growing incidence of such conditions on the worldwide population. A promising avenue is the seconda...

Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing

Pretraining large neural language models, such as BERT, has led to impressive gains on many natural language processing (NLP) tasks. However, most pretraining efforts focus on general domain corpora, such as newswire and Web. A prevailing a...

Long-Acting Nanomedicine for Tuberculosis: A Mechanism-Informed Framework.

Construction and practice of an intelligent management system for preoperative anemia based on multidisciplinary collaboration

[Objective] To improve the efficiency and standardization of preoperative anemia diagnosis and treatment by establishing a systematic intelligent management platform for preoperative anemia. [Methods] A multidisciplinary collaborative model...

A natural language processing based technique for sentiment analysis of college english corpus

The college English corpus can help us better master English, but how to obtain the desired information from a large number of English corpus has become the focus of information technology. Based on the natural language processing (NLP) tec...

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...

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...

Artificial intelligence for vascular minimally invasive surgery: techniques, clinical integration, and challenges.

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...

Content Analysis of Medical Research Articles: A corpus-based study

Introduction: Content analysis applied for comparing texts, a writer’s works with others or the same author, the texts written in a natural language with texts in other languages literature and review of specialized field. The present study...

Biomedical Natural Language Processing

Biomedical Natural Language Processing is a comprehensive tour through the classic and current work in the field. It discusses all subjects from both a rule-based and a machine learning approach, and also describes each subject from the per...

Integrating NLP to Enhance Algorithmic Identification of Metastatic and Castration‐Resistant Prostate Cancer in Large Claims‐Based Studies

ABSTRACT Purpose Accurate classification of prostate cancer (PC) disease states defined by the presence or absence of metastasis and castration resistance (CRPC) is critical but challenging in population‐based research. As chart review is n...

Natural language processing and its future in medicine

If accurate clinical information were available electronically, automated applications could be developed to use this information to improve patient care and lower costs. However, to be fully retrievable, clinical information must be struct...

Positional impact on ocular lens and thyroid radiation doses during feline cranial CT: A thermoluminescent dosimetry study of 70 cases.

Applications and outcomes of virtual reality in inpatient psychiatry: A systematic review.

Tracking discussions of complementary, alternative, and integrative medicine in the context of the COVID-19 pandemic: a month-by-month sentiment analysis of Twitter data

Abstract Background Coronavirus disease 2019 (COVID-19) is a novel infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Despite the paucity of evidence, various complementary, alternative and integr...

Explainable and interpretable artificial intelligence in medicine: a systematic bibliometric review

Abstract This review aims to explore the growing impact of machine learning and deep learning algorithms in the medical field, with a specific focus on the critical issues of explainability and interpretability associated with black-box alg...

Candyflipping and Other Combinations: Identifying Drug–Drug Combinations from an Online Forum

Novel psychoactive substances (NPS) refer to synthetic compounds or derivatives of more widely known substances of abuse that have emerged over the last two decades. Case reports suggest that users combine substances to achieve desired psyc...

An Introduction to Natural Language Processing

Electronically stored clinical documents may contain both structured data and unstructured data. The use of structured clinical data varies by facility, but clinicians are familiar with coded data such as International Classification of Dis...