AI Medical Compendium Topic

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Medical Informatics Applications

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SBLC: a hybrid model for disease named entity recognition based on semantic bidirectional LSTMs and conditional random fields.

BMC medical informatics and decision making
BACKGROUND: Disease named entity recognition (NER) is a fundamental step in information processing of medical texts. However, disease NER involves complex issues such as descriptive modifiers in actual practice. The accurate identification of disease...

Removing Confounding Factors Associated Weights in Deep Neural Networks Improves the Prediction Accuracy for Healthcare Applications.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
The proliferation of healthcare data has brought the opportunities of applying data-driven approaches, such as machine learning methods, to assist diagnosis. Recently, many deep learning methods have been shown with impressive successes in predicting...

Temporal indexing of medical entity in Chinese clinical notes.

BMC medical informatics and decision making
BACKGROUND: The goal of temporal indexing is to select an occurred time or time interval for each medical entity in clinical notes, so that all medical entities can be indexed on a united timeline, which could assist the understanding of clinical not...

Integrating shortest dependency path and sentence sequence into a deep learning framework for relation extraction in clinical text.

BMC medical informatics and decision making
BACKGROUND: Extracting relations between important clinical entities is critical but very challenging for natural language processing (NLP) in the medical domain. Researchers have applied deep learning-based approaches to clinical relation extraction...

A classification framework for exploiting sparse multi-variate temporal features with application to adverse drug event detection in medical records.

BMC medical informatics and decision making
BACKGROUND: Adverse drug events (ADEs) as well as other preventable adverse events in the hospital setting incur a yearly monetary cost of approximately $3.5 billion, in the United States alone. Therefore, it is of paramount importance to reduce the ...

Importance of medical data preprocessing in predictive modeling and risk factor discovery for the frailty syndrome.

BMC medical informatics and decision making
BACKGROUND: Increasing life expectancy results in more elderly people struggling with age related diseases and functional conditions. This poses huge challenges towards establishing new approaches for maintaining health at a higher age. An important ...

Automatically identifying social isolation from clinical narratives for patients with prostate Cancer.

BMC medical informatics and decision making
BACKGROUND: Social isolation is an important social determinant that impacts health outcomes and mortality among patients. The National Academy of Medicine recently recommended that social isolation be documented in electronic health records (EHR). H...