AIMC Topic: Natural Language Processing

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Machine learning in medicine: a practical introduction to natural language processing.

BMC medical research methodology
BACKGROUND: Unstructured text, including medical records, patient feedback, and social media comments, can be a rich source of data for clinical research. Natural language processing (NLP) describes a set of techniques used to convert passages of wri...

CapsTM: capsule network for Chinese medical text matching.

BMC medical informatics and decision making
BACKGROUND: Text Matching (TM) is a fundamental task of natural language processing widely used in many application systems such as information retrieval, automatic question answering, machine translation, dialogue system, reading comprehension, etc....

Transformers-sklearn: a toolkit for medical language understanding with transformer-based models.

BMC medical informatics and decision making
BACKGROUND: Transformer is an attention-based architecture proven the state-of-the-art model in natural language processing (NLP). To reduce the difficulty of beginning to use transformer-based models in medical language understanding and expand the ...

Multi-Sensor Context-Aware Based Chatbot Model: An Application of Humanoid Companion Robot.

Sensors (Basel, Switzerland)
In aspect of the natural language processing field, previous studies have generally analyzed sound signals and provided related responses. However, in various conversation scenarios, image information is still vital. Without the image information, mi...

Multiple Embeddings Enhanced Multi-Graph Neural Networks for Chinese Healthcare Named Entity Recognition.

IEEE journal of biomedical and health informatics
Named Entity Recognition (NER) is a natural language processing task for recognizing named entities in a given sentence. Chinese NER is difficult due to the lack of delimited spaces and conventional features for determining named entity boundaries an...

Gene Mutation Classification through Text Evidence Facilitating Cancer Tumour Detection.

Journal of healthcare engineering
A cancer tumour consists of thousands of genetic mutations. Even after advancement in technology, the task of distinguishing genetic mutations, which act as driver for the growth of tumour with passengers (Neutral Genetic Mutations), is still being d...

Continual learning for recurrent neural networks: An empirical evaluation.

Neural networks : the official journal of the International Neural Network Society
Learning continuously during all model lifetime is fundamental to deploy machine learning solutions robust to drifts in the data distribution. Advances in Continual Learning (CL) with recurrent neural networks could pave the way to a large number of ...

Improved biomedical word embeddings in the transformer era.

Journal of biomedical informatics
BACKGROUND: Recent natural language processing (NLP) research is dominated by neural network methods that employ word embeddings as basic building blocks. Pre-training with neural methods that capture local and global distributional properties (e.g.,...

BioVerbNet: a large semantic-syntactic classification of verbs in biomedicine.

Journal of biomedical semantics
BACKGROUND: Recent advances in representation learning have enabled large strides in natural language understanding; However, verbal reasoning remains a challenge for state-of-the-art systems. External sources of structured, expert-curated verb-relat...

Natural Language Processing to Identify Advance Care Planning Documentation in a Multisite Pragmatic Clinical Trial.

Journal of pain and symptom management
CONTEXT: Large multisite clinical trials studying decision-making when facing serious illness require an efficient method for abstraction of advance care planning (ACP) documentation from clinical text documents. However, the current gold standard me...