AIMC Topic: Machine Learning

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Comparing Precision Machine Learning With Consumer, Quality, and Volume Metrics for Ranking Orthopedic Surgery Hospitals: Retrospective Study.

Journal of medical Internet research
BACKGROUND: Patients' choices of providers when undergoing elective surgeries significantly impact both perioperative outcomes and costs. There exist a variety of approaches that are available to patients for evaluating between different hospital cho...

The influence of machine learning-based knowledge management model on enterprise organizational capability innovation and industrial development.

PloS one
The aims are to explore the construction of the knowledge management model for engineering cost consulting enterprises, and to expand the application of data mining techniques and machine learning methods in constructing knowledge management model. T...

Emergence and organization of adult brain function throughout child development.

NeuroImage
Adult cognitive neuroscience has guided the study of human brain development by identifying regions associated with cognitive functions at maturity. The activity, connectivity, and structure of a region can be compared across ages to characterize the...

MALDI-TOF MS platform combined with machine learning to establish a model for rapid identification of methicillin-resistant Staphylococcus aureus.

Journal of microbiological methods
MALDI-TOF MS is an effective potential tool to distinguish between MSSA and MRSA. By combining the ClinProTools3.0 software and manual grouping intervention, we proposed a model optimization method for the first time. The cross validation of the mode...

Zoom in Lesions for Better Diagnosis: Attention Guided Deformation Network for WCE Image Classification.

IEEE transactions on medical imaging
Wireless capsule endoscopy (WCE) is a novel imaging tool that allows noninvasive visualization of the entire gastrointestinal (GI) tract without causing discomfort to patients. Convolutional neural networks (CNNs), though perform favorably against tr...

A Universal Approximation Result for Difference of Log-Sum-Exp Neural Networks.

IEEE transactions on neural networks and learning systems
We show that a neural network whose output is obtained as the difference of the outputs of two feedforward networks with exponential activation function in the hidden layer and logarithmic activation function in the output node, referred to as log-su...

Circular Complex-Valued GMDH-Type Neural Network for Real-Valued Classification Problems.

IEEE transactions on neural networks and learning systems
Recently, applications of complex-valued neural networks (CVNNs) to real-valued classification problems have attracted significant attention. However, most existing CVNNs are black-box models with poor explanation performance. This study extends the ...

DACH: Domain Adaptation Without Domain Information.

IEEE transactions on neural networks and learning systems
Domain adaptation is becoming increasingly important for learning systems in recent years, especially with the growing diversification of data domains in real-world applications, such as the genetic data from various sequencing platforms and video fe...

A machine learning-based clinical tool for diagnosing myopathy using multi-cohort microarray expression profiles.

Journal of translational medicine
BACKGROUND: Myopathies are a heterogenous collection of disorders characterized by dysfunction of skeletal muscle. In practice, myopathies are frequently encountered by physicians and precise diagnosis remains a challenge in primary care. Molecular e...