AIMC Topic: Deep Learning

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Enhancing Transthyretin Binding Affinity Prediction with a Consensus Model: Insights from the Tox24 Challenge.

Chemical research in toxicology
Transthyretin (TTR) plays a vital role in thyroid hormone transport and homeostasis in both the blood and target tissues. Interactions between exogenous compounds and TTR can disrupt the function of the endocrine system, potentially causing toxicity....

Low-cost video-based air quality estimation system using structured deep learning with selective state space modeling.

Environment international
Air quality is crucial for both public health and environmental sustainability. An efficient and cost-effective model is essential for accurate air quality predictions and proactive pollution control. However, existing research primarily focuses on s...

Phytophagous, blood-suckers or predators? Automated identification of Chagas disease vectors and similar bugs using convolutional neural network algorithms.

Acta tropica
Correct identification of blood-sucking bugs, such as triatomines, is important because they are vectors of Chagas' disease. Identifying these insects is often difficult for non-specialists. Deep learning is emerging as a solution for automated ident...

A deep learning-based multimodal medical imaging model for breast cancer screening.

Scientific reports
In existing breast cancer prediction research, most models rely solely on a single type of imaging data, which limits their performance. To overcome this limitation, the present study explores breast cancer prediction models based on multimodal medic...

A non-invasive diagnostic approach for neuroblastoma utilizing preoperative enhanced computed tomography and deep learning techniques.

Scientific reports
Neuroblastoma presents a wide variety of clinical phenotypes, demonstrating different levels of benignity and malignancy among its subtypes. Early diagnosis is essential for effective patient management. Computed tomography (CT) serves as a significa...

Keystone microbial taxa identified by deep learning reveal mechanisms of phosphorus stoichiometric homeostasis in submerged macrophytes under different hydrodynamic states.

Water research
Phosphorus (P) pollution in aquatic ecosystems triggers eutrophication, disrupting ecological processes. Although phytoremediation using submerged macrophytes is promising, its efficacy depends on plant-microbe interactions and stoichiometric homeost...

Sign potential-driven multiplicative optimization for robust deep reinforcement learning.

Neural networks : the official journal of the International Neural Network Society
Deep Reinforcement Learning (DRL) has attracted the interest of researchers due to its ability to provide valuable solutions to a variety of problems in different fields, such as robotics, autonomous driving, financial trading, and more. However, DRL...

Communication-efficient distributed learning with Local Immediate Error Compensation.

Neural networks : the official journal of the International Neural Network Society
Gradient compression with error compensation has attracted significant attention with the target of reducing the heavy communication overhead in distributed learning. However, existing compression methods either perform only unidirectional compressio...

A multi-task neural network for full waveform ultrasonic bone imaging.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: It is a challenging task to use ultrasound for bone imaging, as the bone tissue has a complex structure with high acoustic impedance and speed-of-sound (SOS). Recently, full waveform inversion (FWI) has shown promising imagi...

Monitoring Amphetamine and Methamphetamine Mixtures Based on Deep Learning Involves Colorimetric Sensing.

Analytical chemistry
Precise recognition and discrimination of highly similar analytes (either in structure or property) with distinguishable sensing responses are challenging but significant in the practical application of drug seizing, food additive inspection, environ...