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Information Storage and Retrieval

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Improving Loanword Identification in Low-Resource Language with Data Augmentation and Multiple Feature Fusion.

Computational intelligence and neuroscience
Loanword identification is studied in recent years to alleviate data sparseness in several natural language processing (NLP) tasks, such as machine translation, cross-lingual information retrieval, and so on. However, recent studies on this topic usu...

Revealing Opinions for COVID-19 Questions Using a Context Retriever, Opinion Aggregator, and Question-Answering Model: Model Development Study.

Journal of medical Internet research
BACKGROUND: COVID-19 has challenged global public health because it is highly contagious and can be lethal. Numerous ongoing and recently published studies about the disease have emerged. However, the research regarding COVID-19 is largely ongoing an...

Cohort profile: St. Michael's Hospital Tuberculosis Database (SMH-TB), a retrospective cohort of electronic health record data and variables extracted using natural language processing.

PloS one
BACKGROUND: Tuberculosis (TB) is a major cause of death worldwide. TB research draws heavily on clinical cohorts which can be generated using electronic health records (EHR), but granular information extracted from unstructured EHR data is limited. T...

Taking a Closed-Book Examination: Decoupling KB-Based Inference by Virtual Hypothesis for Answering Real-World Questions.

Computational intelligence and neuroscience
Complex question answering in real world is a comprehensive and challenging task due to its demand for deeper question understanding and deeper inference. Information retrieval is a common solution and easy to implement, but it cannot answer question...

Automated classification of cancer morphology from Italian pathology reports using Natural Language Processing techniques: A rule-based approach.

Journal of biomedical informatics
Pathology reports represent a primary source of information for cancer registries. Hospitals routinely process high volumes of free-text reports, a valuable source of information regarding cancer diagnosis for improving clinical care and supporting r...

Information retrieval on oncology knowledge base using recursive paraphrase lattice.

Journal of biomedical informatics
For annotation in cancer genomic medicine, oncologists have to refer to various knowledge bases worldwide and retrieve all information (e.g., drugs, clinical trials, and academic papers) related to a gene variant. However, oncologists find it difficu...

CapsField: Light Field-Based Face and Expression Recognition in the Wild Using Capsule Routing.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Light field (LF) cameras provide rich spatio-angular visual representations by sensing the visual scene from multiple perspectives and have recently emerged as a promising technology to boost the performance of human-machine systems such as biometric...

Disease Concept-Embedding Based on the Self-Supervised Method for Medical Information Extraction from Electronic Health Records and Disease Retrieval: Algorithm Development and Validation Study.

Journal of medical Internet research
BACKGROUND: The electronic health record (EHR) contains a wealth of medical information. An organized EHR can greatly help doctors treat patients. In some cases, only limited patient information is collected to help doctors make treatment decisions. ...

Patient Cohort Retrieval using Transformer Language Models.

AMIA ... Annual Symposium proceedings. AMIA Symposium
We apply deep learning-based language models to the task of patient cohort retrieval (CR) with the aim to assess their efficacy. The task ofCR requires the extraction of relevant documents from the electronic health records (EHRs) on the basis of a g...

EffiCare: Better Prognostic Models via Resource-Efficient Health Embeddings.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Recent medical prognostic models adapted from high data-resource fields like language processing have quickly grown in complexity and size. However, since medical data typically constitute low data-resource settings, performances on tasks like clinic...