AIMC Topic: Natural Language Processing

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Natural language processing with machine learning to predict outcomes after ovarian cancer surgery.

Gynecologic oncology
OBJECTIVE: To determine if natural language processing (NLP) with machine learning of unstructured full text documents (a preoperative CT scan) improves the ability to predict postoperative complication and hospital readmission among women with ovari...

Designing an openEHR-Based Pipeline for Extracting and Standardizing Unstructured Clinical Data Using Natural Language Processing.

Methods of information in medicine
BACKGROUND: Merging disparate and heterogeneous datasets from clinical routine in a standardized and semantically enriched format to enable a multiple use of data also means incorporating unstructured data such as medical free texts. Although the ext...

Development of a Portable Tool to Identify Patients With Atrial Fibrillation Using Clinical Notes From the Electronic Medical Record.

Circulation. Cardiovascular quality and outcomes
BACKGROUND: The electronic medical record contains a wealth of information buried in free text. We created a natural language processing algorithm to identify patients with atrial fibrillation (AF) using text alone.

Using the contextual language model BERT for multi-criteria classification of scientific articles.

Journal of biomedical informatics
BACKGROUND: Finding specific scientific articles in a large collection is an important natural language processing challenge in the biomedical domain. Systematic reviews and interactive article search are the type of downstream applications that bene...

Use of Natural Language Processing to Improve Identification of Patients With Peripheral Artery Disease.

Circulation. Cardiovascular interventions
BACKGROUND: Peripheral artery disease (PAD) is underrecognized, undertreated, and understudied: each of these endeavors requires efficient and accurate identification of patients with PAD. Currently, PAD patient identification relies on diagnosis/pro...

Grouping compositions based on similarity of music themes.

PloS one
Finding music pieces whose similarity is explainable in plain musical terms can be of considerable value in many applications. We propose a composition grouping method based on musicological approach. The underlying idea is to compare music notation ...

Sequence-to-function deep learning frameworks for engineered riboregulators.

Nature communications
While synthetic biology has revolutionized our approaches to medicine, agriculture, and energy, the design of completely novel biological circuit components beyond naturally-derived templates remains challenging due to poorly understood design rules....

Low Testosterone on Social Media: Application of Natural Language Processing to Understand Patients' Perceptions of Hypogonadism and Its Treatment.

Journal of medical Internet research
BACKGROUND: Despite the results of the Testosterone Trials, physicians remain uncomfortable treating men with hypogonadism. Discouraged, men increasingly turn to social media to discuss medical concerns.

Question-driven summarization of answers to consumer health questions.

Scientific data
Automatic summarization of natural language is a widely studied area in computer science, one that is broadly applicable to anyone who needs to understand large quantities of information. In the medical domain, automatic summarization has the potenti...