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Robust and generalizable embryo selection based on artificial intelligence and time-lapse image sequences.

PloS one
Assessing and selecting the most viable embryos for transfer is an essential part of in vitro fertilization (IVF). In recent years, several approaches have been made to improve and automate the procedure using artificial intelligence (AI) and deep le...

Beam Damage Assessment Using Natural Frequency Shift and Machine Learning.

Sensors (Basel, Switzerland)
Damage detection based on modal parameter changes has become popular in the last few decades. Nowadays, there are robust and reliable mathematical relations available to predict natural frequency changes if damage parameters are known. Using these re...

Interpretable Model Based on Pyramid Scene Parsing Features for Brain Tumor MRI Image Segmentation.

Computational and mathematical methods in medicine
Due to the black box model nature of convolutional neural networks, computer-aided diagnosis methods based on depth learning are usually poorly interpretable. Therefore, the diagnosis results obtained by these unexplained methods are difficult to gai...

Developing machine learning models for prediction of mortality in the medical intensive care unit.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Alert of patient deterioration is essential for prompt medical intervention in the Medical Intensive Care Unit (MICU). Logistic Regression (LR) has been used for the development of most conventional severity-of-illness scori...

Automated detection of COVID-19 through convolutional neural network using chest x-ray images.

PloS one
The COVID-19 epidemic has a catastrophic impact on global well-being and public health. More than 27 million confirmed cases have been reported worldwide until now. Due to the growing number of confirmed cases, and challenges to the variations of the...

Review on Epileptic Seizure Prediction: Machine Learning and Deep Learning Approaches.

Computational and mathematical methods in medicine
Epileptic seizures occur due to brain abnormalities that can indirectly affect patient's health. It occurs abruptly without any symptoms and thus increases the mortality rate of humans. Almost 1% of world's population suffers from epileptic seizures....

Comparison of DEM Super-Resolution Methods Based on Interpolation and Neural Networks.

Sensors (Basel, Switzerland)
High-resolution digital elevation models (DEMs) play a critical role in geospatial databases, which can be applied to many terrain-related studies such as facility siting, hydrological analysis, and urban design. However, due to the limitation of pre...

WeDea: A New EEG-Based Framework for Emotion Recognition.

IEEE journal of biomedical and health informatics
With the development of sensing technologies and machine learning, techniques that can identify emotions and inner states of a human through physiological signals, known as electroencephalography (EEG), have been actively developed and applied to var...

A Large-Scale Dataset and Deep Learning Model for Detecting and Counting Olive Trees in Satellite Imagery.

Computational intelligence and neuroscience
Since the Pre-Roman era, olive trees have a significant economic and cultural value. In 2019, the Al-Jouf region, in the north of the Kingdom of Saudi Arabia, gained a global presence by entering the Guinness World Records, with the largest number of...

Deep Learning-Based Estimation of Reverberant Environment for Audio Data Augmentation.

Sensors (Basel, Switzerland)
This paper proposes an audio data augmentation method based on deep learning in order to improve the performance of dereverberation. Conventionally, audio data are augmented using a room impulse response, which is artificially generated by some metho...