AIMC Topic: Machine Learning

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A new type of neurons for machine learning.

International journal for numerical methods in biomedical engineering
In machine learning, an artificial neural network is the mainstream approach. Such a network consists of many neurons. These neurons are of the same type characterized by the 2 features: (1) an inner product of an input vector and a matching weightin...

Predicting Ascospore Release of Monilinia vaccinii-corymbosi of Blueberry with Machine Learning.

Phytopathology
Mummy berry, caused by Monilinia vaccinii-corymbosi, causes economic losses of highbush blueberry in the U.S. Pacific Northwest (PNW). Apothecia develop from mummified berries overwintering on soil surfaces and produce ascospores that infect tissue e...

Prediction of early unplanned intensive care unit readmission in a UK tertiary care hospital: a cross-sectional machine learning approach.

BMJ open
OBJECTIVES: Unplanned readmissions to the intensive care unit (ICU) are highly undesirable, increasing variance in care, making resource planning difficult and potentially increasing length of stay and mortality in some settings. Identifying patients...

A deep learning framework for supporting the classification of breast lesions in ultrasound images.

Physics in medicine and biology
In this research, we exploited the deep learning framework to differentiate the distinctive types of lesions and nodules in breast acquired with ultrasound imaging. A biopsy-proven benchmarking dataset was built from 5151 patients cases containing a ...

A deep learning-based multi-model ensemble method for cancer prediction.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Cancer is a complex worldwide health problem associated with high mortality. With the rapid development of the high-throughput sequencing technology and the application of various machine learning methods that have emerged i...

Robust Alternating Low-Rank Representation by joint L- and L-norm minimization.

Neural networks : the official journal of the International Neural Network Society
We propose a robust Alternating Low-Rank Representation (ALRR) model formed by an alternating forward-backward representation process. For forward representation, ALRR first recovers the low-rank PCs and random corruptions by an adaptive local Robust...

Post-boosting of classification boundary for imbalanced data using geometric mean.

Neural networks : the official journal of the International Neural Network Society
In this paper, a novel imbalance learning method for binary classes is proposed, named as Post-Boosting of classification boundary for Imbalanced data (PBI), which can significantly improve the performance of any trained neural networks (NN) classifi...

Deep learning approach to bacterial colony classification.

PloS one
In microbiology it is diagnostically useful to recognize various genera and species of bacteria. It can be achieved using computer-aided methods, which make the recognition processes more automatic and thus significantly reduce the time necessary for...

Automated Analysis of Unregistered Multi-View Mammograms With Deep Learning.

IEEE transactions on medical imaging
We describe an automated methodology for the analysis of unregistered cranio-caudal (CC) and medio-lateral oblique (MLO) mammography views in order to estimate the patient's risk of developing breast cancer. The main innovation behind this methodolog...