AIMC Topic: Algorithms

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Optimal STI controls for HIV patients based on an efficient deep Q learning method.

Journal of theoretical biology
We investigate an efficient computational tool to suggest useful treatment regimens for people infected with the human immunodeficiency virus (HIV). Structured treatment interruption (STI) is a regimen in which therapeutic drugs are periodically admi...

Boosting the performance of molecular property prediction via graph-text alignment and multi-granularity representation enhancement.

Journal of molecular graphics & modelling
Deep learning is playing an increasingly important role in accurate prediction of molecular properties. Prior to being processed by a deep learning model, a molecule is typically represented in the form of a text or a graph. While some methods attemp...

An attribution graph-based interpretable method for CNNs.

Neural networks : the official journal of the International Neural Network Society
Convolutional Neural Networks (CNNs) have demonstrated outstanding performance in various domains, such as face recognition, object detection, and image segmentation. However, the lack of transparency and limited interpretability inherent in CNNs pos...

Human-robot interaction in motor imagery: A system based on the STFCN for unilateral upper limb rehabilitation assistance.

Journal of neuroscience methods
BACKGROUND: Rehabilitation training based on the brain-computer interface of motor imagery (MI-BCI) can help restore the connection between the brain and movement. However, the performance of most popular MI-BCI system is coarse-level, which means th...

Nanoscale single-vesicle analysis: High-throughput approaches through AI-enhanced super-resolution image analysis.

Biosensors & bioelectronics
The analysis of membrane vesicles at the nanoscale level is crucial for advancing the understanding of intercellular communication and its implications for health and disease. Despite their significance, the nanoscale analysis of vesicles at the sing...

A two-stage ensemble learning based prediction and grading model for PD-1/PD-L1 inhibitor-related cardiac adverse events: A multicenter retrospective study.

Computer methods and programs in biomedicine
BACKGROUND: Immune-related cardiac adverse events (ircAEs) caused by programmed cell death protein-1 (PD-1) and programmed death-ligand-1 (PD-L1) inhibitors can lead to fulminant and even fatal consequences. This study aims to develop a prediction an...

Generative artificial intelligence for small molecule drug design.

Current opinion in biotechnology
In recent years, the rapid advancement of generative artificial intelligence (GenAI) has revolutionized the landscape of drug design, offering innovative solutions to potentially expedite the discovery of novel therapeutics. GenAI encompasses algorit...

Development and validation of a two-stage convolutional neural network algorithm for segmentation of MRI white matter hyperintensities for longitudinal studies in CADASIL.

Computers in biology and medicine
BACKGROUND: Segmentation of white matter hyperintensities (WMH) in CADASIL, one of the most severe cerebral small vessel disease of genetic origin, is challenging.

GCGACNN: A Graph Neural Network and Random Forest for Predicting Microbe-Drug Associations.

Biomolecules
The interaction between microbes and drugs encompasses the sourcing of pharmaceutical compounds, microbial drug degradation, the development of , and the impact of on host drug metabolism and immune modulation. These interactions significantly impac...

Deep Learning System for User Identification Using Sensors on Doorknobs.

Sensors (Basel, Switzerland)
Door access control systems are important to protect the security and integrity of physical spaces. Accuracy and speed are important factors that govern their performance. In this paper, we investigate a novel approach to identify users by measuring ...