AIMC Topic: Algorithms

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MRCNN: a deep learning model for regression of genome-wide DNA methylation.

BMC genomics
BACKGROUND: Determination of genome-wide DNA methylation is significant for both basic research and drug development. As a key epigenetic modification, this biochemical process can modulate gene expression to influence the cell differentiation which ...

Development of a Strategy to Predict and Detect Falls Using Wearable Sensors.

Journal of medical systems
Falls are a prevalent problem in actual society. Some falls result in injuries and the cost associated with their treatment is high. This is a complex problem that requires several steps in order to be tackled. Firstly, it is crucial to develop strat...

Entity recognition in Chinese clinical text using attention-based CNN-LSTM-CRF.

BMC medical informatics and decision making
BACKGROUND: Clinical entity recognition as a fundamental task of clinical text processing has been attracted a great deal of attention during the last decade. However, most studies focus on clinical text in English rather than other languages. Recent...

Natural language processing of radiology reports for identification of skeletal site-specific fractures.

BMC medical informatics and decision making
BACKGROUND: Osteoporosis has become an important public health issue. Most of the population, particularly elderly people, are at some degree of risk of osteoporosis-related fractures. Accurate identification and surveillance of patient populations w...

A Supervised Approach to Robust Photoplethysmography Quality Assessment.

IEEE journal of biomedical and health informatics
Early detection of Atrial Fibrillation (AFib) is crucial to prevent stroke recurrence. New tools for monitoring cardiac rhythm are important for risk stratification and stroke prevention. As many of new approaches to long-term AFib detection are now ...

Performing Multi-Target Regression via a Parameter Sharing-Based Deep Network.

International journal of neural systems
Multi-target regression (MTR) comprises the prediction of multiple continuous target variables from a common set of input variables. There are two major challenges when addressing the MTR problem: the exploration of the inter-target dependencies and ...

An unsupervised neuromorphic clustering algorithm.

Biological cybernetics
Brains perform complex tasks using a fraction of the power that would be required to do the same on a conventional computer. New neuromorphic hardware systems are now becoming widely available that are intended to emulate the more power efficient, hi...

Artificial intelligence detection of distal radius fractures: a comparison between the convolutional neural network and professional assessments.

Acta orthopaedica
Background and purpose - Artificial intelligence has rapidly become a powerful method in image analysis with the use of convolutional neural networks (CNNs). We assessed the ability of a CNN, with a fast object detection algorithm previously identify...

Prediction of Long Non-Coding RNAs Based on Deep Learning.

Genes
With the rapid development of high-throughput sequencing technology, a large number of transcript sequences have been discovered, and how to identify long non-coding RNAs (lncRNAs) from transcripts is a challenging task. The identification and inclus...

ML-DSP: Machine Learning with Digital Signal Processing for ultrafast, accurate, and scalable genome classification at all taxonomic levels.

BMC genomics
BACKGROUND: Although software tools abound for the comparison, analysis, identification, and classification of genomic sequences, taxonomic classification remains challenging due to the magnitude of the datasets and the intrinsic problems associated ...