AIMC Topic: Natural Language Processing

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Use of Natural Language Processing (NLP) in Evaluation of Radiology Reports: An Update on Applications and Technology Advances.

Seminars in ultrasound, CT, and MR
Natural language processing (NLP) is focused on the computer interpretation of human language and can be used to evaluate radiology reports and has demonstrated useful applications in essentially all aspects of medical imaging delivery: interpretatio...

ProtPlat: an efficient pre-training platform for protein classification based on FastText.

BMC bioinformatics
BACKGROUND: For the past decades, benefitting from the rapid growth of protein sequence data in public databases, a lot of machine learning methods have been developed to predict physicochemical properties or functions of proteins using amino acid se...

Selection of diagnosis with oncologic relevance information from histopathology free text reports: A machine learning approach.

International journal of medical informatics
Histopathology reports are a primary data source for the case definition phase of a Cancer Registry. By reading the histopathology report, the operator that evaluates an oncology case can define the morphology and topography of cancer, and validate t...

Clinical language search algorithm from free-text: facilitating appropriate imaging.

BMC medical imaging
BACKGROUND: The comprehensiveness and maintenance of the American College of Radiology (ACR) Appropriateness Criteria (AC) makes it a unique resource for evidence-based clinical imaging decision support, but it is underutilized by clinicians. To faci...

Pre-training Model Based on Parallel Cross-Modality Fusion Layer.

PloS one
Visual Question Answering (VQA) is a learning task that combines computer vision with natural language processing. In VQA, it is important to understand the alignment between visual concepts and linguistic semantics. In this paper, we proposed a Pre-...

Disambiguating Clinical Abbreviations Using a One-Fits-All Classifier Based on Deep Learning Techniques.

Methods of information in medicine
BACKGROUND: Abbreviations are considered an essential part of the clinical narrative; they are used not only to save time and space but also to hide serious or incurable illnesses. Misreckoning interpretation of the clinical abbreviations could affec...

Natural language processing for automated surveillance of intraoperative neuromonitoring in spine surgery.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
We sought to develop natural language processing (NLP) methods for automated detection and characterization of neuromonitoring documentation from free-text operative reports in patients undergoing spine surgery. We included 13,718 patients who receiv...

Deep Modular Bilinear Attention Network for Visual Question Answering.

Sensors (Basel, Switzerland)
VQA (Visual Question Answering) is a multi-model task. Given a picture and a question related to the image, it will determine the correct answer. The attention mechanism has become a de facto component of almost all VQA models. Most recent VQA approa...

Identifying Information Gaps in Electronic Health Records by Using Natural Language Processing: Gynecologic Surgery History Identification.

Journal of medical Internet research
BACKGROUND: Electronic health records (EHRs) are a rich source of longitudinal patient data. However, missing information due to clinical care that predated the implementation of EHR system(s) or care that occurred at different medical institutions i...