AIMC Topic: Neural Networks, Computer

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Fast screening of covariates in population models empowered by machine learning.

Journal of pharmacokinetics and pharmacodynamics
One of the objectives of Pharmacometry (PMX) population modeling is the identification of significant and clinically relevant relationships between parameters and covariates. Here, we demonstrate how this complex selection task could benefit from sup...

Towards More Accurate Automatic Sleep Staging via Deep Transfer Learning.

IEEE transactions on bio-medical engineering
BACKGROUND: Despite recent significant progress in the development of automatic sleep staging methods, building a good model still remains a big challenge for sleep studies with a small cohort due to the data-variability and data-inefficiency issues....

Development of a Wearable Camera and AI Algorithm for Medication Behavior Recognition.

Sensors (Basel, Switzerland)
As many as 40% to 50% of patients do not adhere to long-term medications for managing chronic conditions, such as diabetes or hypertension. Limited opportunity for medication monitoring is a major problem from the perspective of health professionals....

Permutation-based identification of important biomarkers for complex diseases via machine learning models.

Nature communications
Study of human disease remains challenging due to convoluted disease etiologies and complex molecular mechanisms at genetic, genomic, and proteomic levels. Many machine learning-based methods have been developed and widely used to alleviate some anal...

Comprehensive influence of topological location and neighbor information on identifying influential nodes in complex networks.

PloS one
Identifying the influential nodes of complex networks is now seen as essential for optimizing the network structure or efficiently disseminating information through networks. Most of the available methods determine the spreading capability of nodes b...

MD-UNET: Multi-input dilated U-shape neural network for segmentation of bladder cancer.

Computational biology and chemistry
Accurate segmentation of the tumour area is crucial for the treatment and prognosis of patients with bladder cancer. However, the complex information from the MRI image poses an important challenge for us to accurately segment the lesion, for example...

Integrative learning for population of dynamic networks with covariates.

NeuroImage
Although there is a rapidly growing literature on dynamic connectivity methods, the primary focus has been on separate network estimation for each individual, which fails to leverage common patterns of information. We propose novel graph-theoretic ap...

Comparative Study of Deep Generative Models on Chemical Space Coverage.

Journal of chemical information and modeling
In recent years, deep molecular generative models have emerged as promising methods for molecular design. Thanks to the rapid advance of deep learning techniques, deep learning architectures such as recurrent neural networks, variational autoencoder...

Aesthetic preference for art can be predicted from a mixture of low- and high-level visual features.

Nature human behaviour
It is an open question whether preferences for visual art can be lawfully predicted from the basic constituent elements of a visual image. Here, we developed and tested a computational framework to investigate how aesthetic values are formed. We show...

Device-Free Human Activity Recognition with Low-Resolution Infrared Array Sensor Using Long Short-Term Memory Neural Network.

Sensors (Basel, Switzerland)
Sensor-based human activity recognition (HAR) has attracted enormous interests due to its wide applications in the Internet of Things (IoT), smart homes and healthcare. In this paper, a low-resolution infrared array sensor-based HAR approach is propo...