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Biomedical Research

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Using Neural Networks for Relation Extraction from Biomedical Literature.

Methods in molecular biology (Clifton, N.J.)
Using different sources of information to support automated extracting of relations between biomedical concepts contributes to the development of our understanding of biological systems. The primary comprehensive source of these relations is biomedic...

Machine Learning for Biomedical Time Series Classification: From Shapelets to Deep Learning.

Methods in molecular biology (Clifton, N.J.)
With the biomedical field generating large quantities of time series data, there has been a growing interest in developing and refining machine learning methods that allow its mining and exploitation. Classification is one of the most important and c...

Predictive modeling in reproductive medicine: Where will the future of artificial intelligence research take us?

Fertility and sterility
Artificial intelligence (AI) systems have been proposed for reproductive medicine since 1997. Although AI is the main driver of emergent technologies in reproduction, such as robotics, Big Data, and internet of things, it will continue to be the engi...

Big Data Approaches in Heart Failure Research.

Current heart failure reports
PURPOSE OF REVIEW: The goal of this review is to summarize the state of big data analyses in the study of heart failure (HF). We discuss the use of big data in the HF space, focusing on "omics" and clinical data. We address some limitations of this d...

Enhancing scientific discoveries in molecular biology with deep generative models.

Molecular systems biology
Generative models provide a well-established statistical framework for evaluating uncertainty and deriving conclusions from large data sets especially in the presence of noise, sparsity, and bias. Initially developed for computer vision and natural l...

Accelerating ophthalmic artificial intelligence research: the role of an open access data repository.

Current opinion in ophthalmology
PURPOSE OF REVIEW: Artificial intelligence has already provided multiple clinically relevant applications in ophthalmology. Yet, the explosion of nonstandardized reporting of high-performing algorithms are rendered useless without robust and streamli...

A NICE perspective on computable biomedical knowledge.

BMJ health & care informatics
INTRODUCTION: The National Institute for Health and Care Excellence (NICE) plays a central role in the NHS. We distill knowledge of best practice from the best available sources of evidence and share this across the health and care system, typically ...

Does not compute: challenges and solutions in managing computable biomedical knowledge.

BMJ health & care informatics
Computers can potentially play a key role in resolving knowledge mobilisation bottlenecks in health and care through decision support at the point of care based on computable biomedical knowledge (CBK). But the management of CBK comes with a range of...

HDR UK supporting mobilising computable biomedical knowledge in the UK.

BMJ health & care informatics
Computable biomedical knowledge (CBK) represents an evolving area of health informatics, with potential for rapid translational patient benefit. Health Data Research UK (HDR UK) is the national Institute for Health Data Science, whose aim is to unite...