Drug resistance remains one of the primary challenges in effective cancer therapy. In this study, we employed a deep neural network (DNN)-based transfer learning (TL) approach to predict drug response and uncover drug resistance mechanisms. We integr...
To address the long-standing challenges children with autism face in social skills and emotional regulation, this study introduces Emotion-based Music Intelligent Network (EmoMusik-Net)-a deep learning model designed for intelligent music therapy. Th...
Multiplexed imaging has transformed our ability to study tissue organization by capturing thousands of cells and molecules in their native context. However, these datasets are enormous, often comprising tens of gigabytes per image, and require comple...
DNA molecules can be used to build "neural networks" that function like the brain, enabling them to perform complex computational tasks. However, a fundamental limitation of existing DNA networks is that their most basic computing units cannot perfor...
BACKGROUND: The application of deep learning techniques in cephalometric analysis has become increasingly prominent. Although automatic landmarking models for cephalometric analysis have been developed, their accuracy still requires validation and re...
PURPOSE OF REVIEW: Accurate, timely quantification of cardiac function is central to the diagnosis, management, and monitoring of cardiovascular disease. This review synthesizes recent advances in artificial intelligence (AI) applications across the ...
Chemical communications (Cambridge, England)
Nov 27, 2025
AI-based protein design can rapidly generate thousands of candidate binders, but most fail to fold or bind productively, creating a critical need for robust prioritization. We present a generalizable hybrid pipeline that integrates deep-learning desi...
Phenotypic drug screening remains constrained by the vastness of chemical space and the technical challenges of scaling experimental workflows. To overcome these barriers, computational methods have been developed to prioritize compounds, but they re...
International journal of neural systems
Nov 26, 2025
Machine learning, deep learning and neural networks are extensively developed in many fields, with neural networks playing an important role in a wide variety of applications. However, a sufficient explanation of the structure and functionality of co...
BACKGROUND: Accurate landmark localization is important for three-dimensional (3D) cephalometric analysis. Although deep learning has shown promising performance for 3D landmark localization, the high computational burden of processing volumetric dat...
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