AIMC Topic: Deep Learning

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A unified deep-learning framework for enhanced patient-specific quality assurance of intensity-modulated radiation therapy plans.

Medical physics Dec 24, 2024
BACKGROUND: Modern radiation therapy techniques, such as intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT), use complex fluence modulation strategies to achieve optimal patient dose distribution. Ensuring their ...
Radiotherapy Dosage Radiotherapy, Intensity-Modulated Humans Deep Learning Radiotherapy Planning, Computer-Assisted Quality Assurance, Health Care
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Topology-based protein classification: A deep learning approach.

Biochemical and biophysical research communications Dec 24, 2024
Utilizing Artificial Intelligence (AI) in computational biology techniques could offer significant advantages in alleviating the growing workloads faced by structural biologists, especially with the emergence of big data. In this study, we employed D...
Protein Conformation Deep Learning Proteins Neural Networks, Computer Computational Biology Databases, Protein
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A feature fusion method based on radiomic features and revised deep features for improving tumor prediction in ultrasound images.

Computers in biology and medicine Dec 24, 2024
BACKGROUND: Radiomic features and deep features are both vitally helpful for the accurate prediction of tumor information in breast ultrasound. However, whether integrating radiomic features and deep features can improve the prediction performance of...
Image Interpretation, Computer-Assisted ROC Curve Ultrasonography, Mammary Humans Neural Networks, Computer Female Radiomics Deep Learning Breast Neoplasms Ultrasonography
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Development of Nipple Trauma Evaluation System With Deep Learning.

Journal of human lactation : official journal of International Lactation Consultant Association Dec 24, 2024
BACKGROUND: No research has been conducted on the use of deep learning for breastfeeding support.
Nipples Japan Breast Feeding Female Deep Learning Humans
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Mask R-CNN assisted diagnosis of spinal tuberculosis.

Journal of X-ray science and technology Dec 24, 2024
The prevalence of spinal tuberculosis (ST) is particularly high in underdeveloped regions with inadequate medical conditions. This not only leads to misdiagnosis and delays in treatment progress but also contributes to the continued transmission of t...
Deep Learning Tomography, X-Ray Computed Humans Diagnosis, Computer-Assisted Tuberculosis, Spinal Neural Networks, Computer
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Multimodal data-based human motion intention prediction using adaptive hybrid deep learning network for movement challenged person.

Scientific reports Dec 24, 2024
Recently, social demands for a good quality of life have increased among the elderly and disabled people. So, biomedical engineers and robotic researchers aimed to fuse these techniques in a novel rehabilitation system. Moreover, these models utilize...
Algorithms Deep Learning Electromyography Intention Electroencephalography Humans Neural Networks, Computer Movement
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Longitudinal interpretability of deep learning based breast cancer risk prediction.

Physics in medicine and biology Dec 24, 2024
Deep-learning-based models have achieved state-of-the-art breast cancer risk (BCR) prediction performance. However, these models are highly complex, and the underlying mechanisms of BCR prediction are not fully understood. Key questions include wheth...
Longitudinal Studies Mammography Female Breast Neoplasms Risk Assessment Deep Learning Humans Middle Aged
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Automated treatment planning with deep reinforcement learning for head-and-neck (HN) cancer intensity modulated radiation therapy (IMRT).

Physics in medicine and biology Dec 24, 2024
To develop a deep reinforcement learning (DRL) agent to self-interact with the treatment planning system to automatically generate intensity modulated radiation therapy (IMRT) treatment plans for head-and-neck (HN) cancer with consistent organ-at-ris...
Humans Deep Learning Head and Neck Neoplasms Automation Radiotherapy Dosage Radiotherapy, Intensity-Modulated Organs at Risk Radiotherapy Planning, Computer-Assisted
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EnDM-CPP: A Multi-view Explainable Framework Based on Deep Learning and Machine Learning for Identifying Cell-Penetrating Peptides with Transformers and Analyzing Sequence Information.

Interdisciplinary sciences, computational life sciences Dec 23, 2024
Cell-Penetrating Peptides (CPPs) are a crucial carrier for drug delivery. Since the process of synthesizing new CPPs in the laboratory is both time- and resource-consuming, computational methods to predict potential CPPs can be used to find CPPs to e...
Humans Neural Networks, Computer Machine Learning Computational Biology Amino Acid Sequence Algorithms Cell-Penetrating Peptides Deep Learning
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Identification of STAT3 phosphorylation inhibitors using generative deep learning, virtual screening, molecular dynamics simulations, and biological evaluation for non-small cell lung cancer therapy.

Molecular diversity Dec 23, 2024
The development of phosphorylation-suppressing inhibitors targeting Signal Transducer and Activator of Transcription 3 (STAT3) represents a promising therapeutic strategy for non-small cell lung cancer (NSCLC). In this study, a generative model was d...
STAT3 Transcription Factor Binding Sites Lung Neoplasms Antineoplastic Agents Protein Binding Deep Learning Phosphorylation Humans Carcinoma, Non-Small-Cell Lung Cell Line, Tumor Molecular Dynamics Simulation Molecular Docking Simulation
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