AI Medical Compendium Topic:
Data Mining

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Recurrent neural networks for classifying relations in clinical notes.

Journal of biomedical informatics
We proposed the first models based on recurrent neural networks (more specifically Long Short-Term Memory - LSTM) for classifying relations from clinical notes. We tested our models on the i2b2/VA relation classification challenge dataset. We showed ...

Classification and analysis of a large collection of in vivo bioassay descriptions.

PLoS computational biology
Testing potential drug treatments in animal disease models is a decisive step of all preclinical drug discovery programs. Yet, despite the importance of such experiments for translational medicine, there have been relatively few efforts to comprehens...

A statistical framework for biomedical literature mining.

Statistics in medicine
In systems biology, it is of great interest to identify new genes that were not previously reported to be associated with biological pathways related to various functions and diseases. Identification of these new pathway-modulating genes does not onl...

Leveraging syntax to better capture the semantics of elliptical coordinated compound noun phrases.

Journal of biomedical informatics
Full-text scientific articles are increasingly available, but capturing the meaning conveyed within an article automatically remains a bottleneck for semantic search and reasoning systems. In this paper we consider elliptical coordinated compound nou...

Automated robot-assisted surgical skill evaluation: Predictive analytics approach.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Surgical skill assessment has predominantly been a subjective task. Recently, technological advances such as robot-assisted surgery have created great opportunities for objective surgical evaluation. In this paper, we introduce a predicti...

Data- and expert-driven rule induction and filtering framework for functional interpretation and description of gene sets.

Journal of biomedical semantics
BACKGROUND: High-throughput methods in molecular biology provided researchers with abundance of experimental data that need to be interpreted in order to understand the experimental results. Manual methods of functional gene/protein group interpretat...

Artificial intelligence in healthcare: past, present and future.

Stroke and vascular neurology
Artificial intelligence (AI) aims to mimic human cognitive functions. It is bringing a paradigm shift to healthcare, powered by increasing availability of healthcare data and rapid progress of analytics techniques. We survey the current status of AI ...

Data mining and pathway analysis of glucose-6-phosphate dehydrogenase with natural language processing.

Molecular medicine reports
Human glucose-6-phosphate dehydrogenase (G6PD) is a crucial enzyme in the pentose phosphate pathway, and serves an important role in biosynthesis and the redox balance. G6PD deficiency is a major cause of neonatal jaundice and acute hemolyticanemia, ...

A Two-Stage Biomedical Event Trigger Detection Method Integrating Feature Selection and Word Embeddings.

IEEE/ACM transactions on computational biology and bioinformatics
Extracting biomedical events from biomedical literature plays an important role in the field of biomedical text mining, and the trigger detection is a key step in biomedical event extraction. We propose a two-stage method for trigger detection, which...

Using multiclass classification to automate the identification of patient safety incident reports by type and severity.

BMC medical informatics and decision making
BACKGROUND: Approximately 10% of admissions to acute-care hospitals are associated with an adverse event. Analysis of incident reports helps to understand how and why incidents occur and can inform policy and practice for safer care. Unfortunately ou...