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Probability

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Breast Cancer Classification from Ultrasound Images Using Probability-Based Optimal Deep Learning Feature Fusion.

Sensors (Basel, Switzerland)
After lung cancer, breast cancer is the second leading cause of death in women. If breast cancer is detected early, mortality rates in women can be reduced. Because manual breast cancer diagnosis takes a long time, an automated system is required for...

Using deep learning to predict the outcome of live birth from more than 10,000 embryo data.

BMC pregnancy and childbirth
BACKGROUND: Recently, the combination of deep learning and time-lapse imaging provides an objective, standard and scientific solution for embryo selection. However, the reported studies were based on blastocyst formation or clinical pregnancy as the ...

Effective TCP Flow Management Based on Hierarchical Feedback Learning in Complex Data Center Network.

Sensors (Basel, Switzerland)
Many studies focusing on improving Transmission Control Protocol (TCP) flow control realize a more effective use of bandwidth in data center networks. They are excellent ways to more effectively use the bandwidth between clients and back-end servers....

Dissipativity-Based Disturbance Attenuation Control for T-S Fuzzy Markov Jumping Systems With Nonlinear Multisource Uncertainties and Partly Unknown Transition Probabilities.

IEEE transactions on cybernetics
This article is concerned with the dissipativity-based disturbance attenuation control for a class of Takagi-Sugeno (T-S) fuzzy Markov jump systems (FMJSs) suffering from nonlinear multisource disturbances. The considered system possesses nonlinear a...

Overtaking risk modeling in two-lane two-way highway with heterogeneous traffic environment of a low-income country using naturalistic driving dataset.

Journal of safety research
INTRODUCTION: Driver behavior related to overtaking maneuvers, which are considered a major safety risk determinant on two-lane two-way highway in low- and middle-income countries (LMIC), are an important subject of further analysis. This study evalu...

Human Factor Risk Modeling for Shipyard Operation by Mapping Fuzzy Fault Tree into Bayesian Network.

International journal of environmental research and public health
The operational activities conducted in a shipyard are exposed to high risk associated with human factors. To investigate human factors involved in shipyard operational accidents, a double-nested model was proposed in the present study. The modified ...

DeepCME: A deep learning framework for computing solution statistics of the chemical master equation.

PLoS computational biology
Stochastic models of biomolecular reaction networks are commonly employed in systems and synthetic biology to study the effects of stochastic fluctuations emanating from reactions involving species with low copy-numbers. For such models, the Kolmogor...

Determination of probability of causative pathogen in infectious keratitis using deep learning algorithm of slit-lamp images.

Scientific reports
Corneal opacities are important causes of blindness, and their major etiology is infectious keratitis. Slit-lamp examinations are commonly used to determine the causative pathogen; however, their diagnostic accuracy is low even for experienced ophtha...

Improving random forest predictions in small datasets from two-phase sampling designs.

BMC medical informatics and decision making
BACKGROUND: While random forests are one of the most successful machine learning methods, it is necessary to optimize their performance for use with datasets resulting from a two-phase sampling design with a small number of cases-a common situation i...