AIMC Topic: Information Storage and Retrieval

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Temporal information extraction with the scalable cross-sentence context for electronic health records.

Journal of biomedical informatics
Temporal information is essential for accurate understanding of medical information hidden in electronic health record texts. In the absence of temporal information, it is even impossible to distinguish whether the mentioned symptom is a current cond...

An Experimental Study of Neural Approaches to Multi-Hop Inference in Question Answering.

International journal of neural systems
Question answering aims at computing the answer to a question given a context with facts. Many proposals focus on questions whose answer is explicit in the context; lately, there has been an increasing interest in questions whose answer is not explic...

A deep-learning system bridging molecule structure and biomedical text with comprehension comparable to human professionals.

Nature communications
To accelerate biomedical research process, deep-learning systems are developed to automatically acquire knowledge about molecule entities by reading large-scale biomedical data. Inspired by humans that learn deep molecule knowledge from versatile rea...

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...

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...

Multi-Modal Song Mood Detection with Deep Learning.

Sensors (Basel, Switzerland)
The production and consumption of music in the contemporary era results in big data generation and creates new needs for automated and more effective management of these data. Automated music mood detection constitutes an active task in the field of ...

Dual Position Relationship Transformer for Image Captioning.

Big data
Employing feature vectors extracted from the target detector has been shown to be effective in improving the performance of image captioning. However, it is considered that existing framework suffers from the deficiency of insufficient information ex...

Composition-driven symptom phrase recognition for Chinese medical consultation corpora.

BMC medical informatics and decision making
BACKGROUND: Symptom phrase recognition is essential to improve the use of unstructured medical consultation corpora for the development of automated question answering systems. A majority of previous works typically require enough manually annotated ...

Leveraging medical context to recommend semantically similar terms for chart reviews.

BMC medical informatics and decision making
BACKGROUND: Information retrieval (IR) help clinicians answer questions posed to large collections of electronic medical records (EMRs), such as how best to identify a patient's cancer stage. One of the more promising approaches to IR for EMRs is to ...