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scHiCyclePred: a deep learning framework for predicting cell cycle phases from single-cell Hi-C data using multi-scale interaction information.

The emergence of single-cell Hi-C (scHi-C) technology has provided unprecedented opportunities for i...

Strain-Temperature Dual Sensor Based on Deep Learning Strategy for Human-Computer Interaction Systems.

Thermoelectric (TE) hydrogels, mimicking human skin, possessing temperature and strain sensing capab...

QCL Infrared Spectroscopy Combined with Machine Learning as a Useful Tool for Classifying Acetaminophen Tablets by Brand.

The development of new methods of identification of active pharmaceutical ingredients (API) is a sub...

Interpretable machine learning guided by physical mechanisms reveals drivers of runoff under dynamic land use changes.

Human activities continuously impact water balances and cycling in watersheds, making it essential t...

Intelligent systems in healthcare: A systematic survey of explainable user interfaces.

With radiology shortages affecting over half of the global population, the potential of artificial i...

YOLOv7-Branch: A Jujube Leaf Branch Detection Model for Agricultural Robot.

The intelligent harvesting technology for jujube leaf branches presents a novel avenue for enhancing...

DeepDRA: Drug repurposing using multi-omics data integration with autoencoders.

Cancer treatment has become one of the biggest challenges in the world today. Different treatments a...

BiRNN-DDI: A Drug-Drug Interaction Event Type Prediction Model Based on Bidirectional Recurrent Neural Network and Graph2Seq Representation.

Research on drug-drug interaction (DDI) prediction, particularly in identifying DDI event types, is ...

Integration of Tracking, Re-Identification, and Gesture Recognition for Facilitating Human-Robot Interaction.

For successful human-robot collaboration, it is crucial to establish and sustain quality interaction...

Adaptive self-supervised learning for sequential recommendation.

Sequential recommendation typically utilizes deep neural networks to mine rich information in intera...

Transcriptionally Conditional Recurrent Neural Network for De Novo Drug Design.

Computational molecular generation methods that generate chemical structures from gene expression pr...

PLMACPred prediction of anticancer peptides based on protein language model and wavelet denoising transformation.

Anticancer peptides (ACPs) perform a promising role in discovering anti-cancer drugs. The growing re...

Machine learning and explainable artificial intelligence for the prevention of waterborne cryptosporidiosis and giardiosis.

Cryptosporidium and Giardia are important parasitic protozoa due to their zoonotic potential and imp...

A Human-AI interaction paradigm and its application to rhinocytology.

This article explores Human-Centered Artificial Intelligence (HCAI) in medical cytology, with a focu...

HydraScreen: A Generalizable Structure-Based Deep Learning Approach to Drug Discovery.

We propose HydraScreen, a deep-learning framework for safe and robust accelerated drug discovery. Hy...

Efficient Deep Model Ensemble Framework for Drug-Target Interaction Prediction.

Accurate prediction of Drug-Target Interactions (DTI) is crucial for drug development. Current state...

Application and performance enhancement of FAIMS spectral data for deep learning analysis using generative adversarial network reinforcement.

When using High-field asymmetric ion mobility spectrometry (FAIMS) to process complex mixtures for d...

Gtie-Rt: A comprehensive graph learning model for predicting drugs targeting metabolic pathways in human.

Drugs often target specific metabolic pathways to produce a therapeutic effect. However, these pathw...

Machine learning in preclinical drug discovery.

Drug-discovery and drug-development endeavors are laborious, costly and time consuming. These progra...

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