AIMC Topic: Natural Language Processing

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Exploring chemical space using natural language processing methodologies for drug discovery.

Drug discovery today
Text-based representations of chemicals and proteins can be thought of as unstructured languages codified by humans to describe domain-specific knowledge. Advances in natural language processing (NLP) methodologies in the processing of spoken languag...

Multiple features for clinical relation extraction: A machine learning approach.

Journal of biomedical informatics
Relation extraction aims to discover relational facts about entity mentions from plain texts. In this work, we focus on clinical relation extraction; namely, given a medical record with mentions of drugs and their attributes, we identify relations be...

Semi-Automated evidence synthesis in health psychology: current methods and future prospects.

Health psychology review
The evidence base in health psychology is vast and growing rapidly. These factors make it difficult (and sometimes practically impossible) to consider all available evidence when making decisions about the state of knowledge on a given phenomenon (e....

Deep Learning for Natural Language Processing in Radiology-Fundamentals and a Systematic Review.

Journal of the American College of Radiology : JACR
PURPOSE: Natural language processing (NLP) enables conversion of free text into structured data. Recent innovations in deep learning technology provide improved NLP performance. We aimed to survey deep learning NLP fundamentals and review radiology-r...

Inorganic Materials Synthesis Planning with Literature-Trained Neural Networks.

Journal of chemical information and modeling
Leveraging new data sources is a key step in accelerating the pace of materials design and discovery. To complement the strides in synthesis planning driven by historical, experimental, and computed data, we present an automated, unsupervised method ...

Systematic Evaluation of Research Progress on Natural Language Processing in Medicine Over the Past 20 Years: Bibliometric Study on PubMed.

Journal of medical Internet research
BACKGROUND: Natural language processing (NLP) is an important traditional field in computer science, but its application in medical research has faced many challenges. With the extensive digitalization of medical information globally and increasing i...

Evaluation of the predictive ability of ultrasound-based assessment of breast cancer using BI-RADS natural language reporting against commercial transcriptome-based tests.

PloS one
PURPOSE: The objective of this study was to assess the classification capability of Breast Imaging Reporting and Data System (BI-RADS) ultrasound feature descriptors targeting established commercial transcriptomic gene signatures that guide managemen...

Deep Natural Language Processing Identifies Variation in Care Preference Documentation.

Journal of pain and symptom management
CONTEXT: Documentation of care preferences within 48 hours of admission to an intensive care unit (ICU) is a National Quality Forum-endorsed quality metric for older adults. Care preferences are poorly captured by administrative data.

Multi-Rule Based Ensemble Feature Selection Model for Sarcasm Type Detection in Twitter.

Computational intelligence and neuroscience
Sentimental analysis aims at inferring how people express their opinion over any piece of text or topic of interest. This article deals with detection of an implicit form of the sentiment, referred to as sarcasm. Sarcasm conveys the opposite of what ...