AIMC Topic: Deep Learning
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Pollen morphology, deep learning, phylogenetics, and the evolution of environmental adaptations in Podocarpus.
The New phytologist
Jun 3, 2025
Podocarpus pollen morphology is shaped by both phylogenetic history and the environment. We analyzed the relationship between pollen traits quantified using deep learning and environmental factors within a comparative phylogenetic framework. We inves...
Explainable RNA-Small Molecule Binding Affinity Prediction Based on Multiview Enhancement Learning.
Journal of chemical information and modeling
Jun 3, 2025
RNA has the potential to serve as a drug target, requiring RNA-small molecule binding affinity to screen potential drugs generally. However, accurately predicting RNA-small molecule binding affinity remains a highly challenging task. This study propo...
DeepGFT: identifying spatial domains in spatial transcriptomics of complex and 3D tissue using deep learning and graph Fourier transform.
Genome biology
Jun 3, 2025
The rapid advancements in spatially resolved transcriptomics (SRT) enable the characterization of gene expressions while preserving spatial information. However, high dropout rates and noise hinder accurate spatial domain identification for understan...
Investigating the effect of transformer encoder architecture to improve the reliability of classroom observation ratings on high-inference discourse.
Behavior research methods
Jun 3, 2025
This study investigates the effect of transformer encoder architecture on the classification accuracy of high-inference discourse elements in classroom settings. Recognizing the importance of capturing nuanced interactions between students and teache...
Predicting drug-target interactions using machine learning with improved data balancing and feature engineering.
Scientific reports
Jun 3, 2025
Drug-Target Interaction (DTI) prediction is a vital task in drug discovery, yet it faces significant challenges such as data imbalance and the complexity of biochemical representations. This study makes several contributions to address these issues, ...
Deep learning-based electrical impedance spectroscopy analysis for malignant and potentially malignant oral disorder detection.
Scientific reports
Jun 3, 2025
Electrical impedance spectroscopy (EIS) is a powerful tool used to investigate the properties of materials and biological tissues. This study presents one of the first applications of EIS for the detection and classification of oral potentially malig...
Multimodal deep learning for chemical toxicity prediction and management.
Scientific reports
Jun 3, 2025
The accurate prediction of chemical toxicity is a crucial research focus in chemistry, biotechnology, and national defense. The development of comprehensive datasets for chemical toxicity prediction remains limited due to security constraints and the...
Energy consumption analysis and prediction in exercise training based on accelerometer sensors and deep learning.
Scientific reports
Jun 3, 2025
This study aims to enhance the accuracy and efficiency of energy consumption prediction during exercise training and address the limitations of existing methods in terms of data feature extraction, model complexity, and adaptability to practical appl...
Use of deep learning-based NLP models for full-text data elements extraction for systematic literature review tasks.
Scientific reports
Jun 3, 2025
Systematic literature review (SLR) is an important tool for Health Economics and Outcomes Research (HEOR) evidence synthesis. SLRs involve the identification and selection of pertinent publications and extraction of relevant data elements from full-t...
FPA-based weighted average ensemble of deep learning models for classification of lung cancer using CT scan images.
Scientific reports
Jun 3, 2025
Cancer is among the most dangerous diseases contributing to rising global mortality rates. Lung cancer, particularly adenocarcinoma, is one of the deadliest forms and severely impacts human life. Early diagnosis and appropriate treatment significantl...
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