AIMC Topic: Neural Networks, Computer

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DMHGNN: Double multi-view heterogeneous graph neural network framework for drug-target interaction prediction.

Artificial intelligence in medicine
Accurate identification of drug-target interactions (DTIs) plays a crucial role in drug discovery. Compared with traditional experimental methods that are labor-intensive and time-consuming, computational methods for drug-target interactions predicti...

Predicting the effects of drugs and unveiling their mechanisms of action using an interpretable pharmacodynamic mechanism knowledge graph (IPM-KG).

Computers in biology and medicine
BACKGROUND: Multiple studies have aimed to consolidate drug-related data and predict drug effects. However, most of these studies have focused on integrating diverse data through correlation rather than representing them based on the pharmacodynamic ...

Low-dimensional neural ordinary differential equations accounting for inter-individual variability implemented in Monolix and NONMEM.

CPT: pharmacometrics & systems pharmacology
Neural ordinary differential equations (NODEs) are an emerging machine learning (ML) method to model pharmacometric (PMX) data. Combining mechanism-based components to describe "known parts" and neural networks to learn "unknown parts" is a promising...

Convolutional neural network for colorimetric glucose detection using a smartphone and novel multilayer polyvinyl film microfluidic device.

Scientific reports
Detecting glucose levels is crucial for diabetes patients as it enables timely and effective management, preventing complications and promoting overall health. In this endeavor, we have designed a novel, affordable point-of-care diagnostic device uti...

Semantic-spatial feature-fused cortical surface parcellation: a scale-unified spatial learning network with boundary contrastive loss.

Medical & biological engineering & computing
The cortical surface parcellation provides prior guidance for studying mental disorders and human cognition. Graph neural networks (GNNs) have gained popularity in this task to preserve its spatial structure. However, previous GNNs struggled to effec...

Hessian-based mixed-precision quantization with transition aware training for neural networks.

Neural networks : the official journal of the International Neural Network Society
Model quantization is widely used to realize the promise of ubiquitous embedded deep network inference. While mixed-precision quantization has shown promising performance, existing approaches often rely on time-consuming search process to determine t...

Enhancing urban flow prediction via mutual reinforcement with multi-scale regional information.

Neural networks : the official journal of the International Neural Network Society
Intelligent Transportation Systems (ITS) are essential for modern urban development, with urban flow prediction being a key component. Accurate flow prediction optimizes routes and resource allocation, benefiting residents, businesses, and the enviro...

Recognition of autism in subcortical brain volumetric images using autoencoding-based region selection method and Siamese Convolutional Neural Network.

International journal of medical informatics
BACKGROUND: Autism Spectrum Disorder (ASD) is a neurodevelopmental condition that affects social interactions and behavior. Accurate and early diagnosis of ASD is still challenging even with the improvements in neuroimaging technology and machine lea...

Augmenting a spine CT scans dataset using VAEs, GANs, and transfer learning for improved detection of vertebral compression fractures.

Computers in biology and medicine
In recent years, deep learning has become a popular tool to analyze and classify medical images. However, challenges such as limited data availability, high labeling costs, and privacy concerns remain significant obstacles. As such, generative models...

Mobile Accelerometer Applications in Core Muscle Rehabilitation and Pre-Operative Assessment.

Sensors (Basel, Switzerland)
Individual physiotherapy is crucial in treating patients with various pain and health issues, and significantly impacts abdominal surgical outcomes and further medical problems. Recent technological and artificial intelligent advancements have equipp...