AIMC Topic: Deep Learning

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DeepBP: A transformer-based model for identifying blood-brain barrier penetrating peptides with data augmentation using feedback GAN.

Journal of advanced research
INTRODUCTION: The blood-brain barrier (BBB) serves as a critical structural barrier and impedes the entry of most neurotherapeutic drugs into the brain. This poses substantial challenges for central nervous system (CNS) drug development, as there is ...

A Deep Learning-Based Framework for Predicting Intracerebral Hematoma Expansion Using Head Non-contrast CT Scan.

Academic radiology
RATIONALE AND OBJECTIVES: Hematoma expansion (HE) in intracerebral hemorrhage (ICH) is a critical factor affecting patient outcomes, yet effective clinical tools for predicting HE are currently lacking. We aim to develop a fully automated framework b...

Preoperative Prediction of Axillary Lymph Node Metastasis in Patients With Breast Cancer Through Multimodal Deep Learning Based on Ultrasound and Magnetic Resonance Imaging Images.

Academic radiology
RATIONALE AND OBJECTIVES: Deep learning can enhance the performance of multimodal image analysis, which is known for its noninvasive attributes and complementary efficacy, in predicting axillary lymph node (ALN) metastasis. Therefore, we established ...

Multi-step framework for glaucoma diagnosis in retinal fundus images using deep learning.

Medical & biological engineering & computing
Glaucoma is one of the most common causes of blindness in the world. Screening glaucoma from retinal fundus images based on deep learning is a common method at present. In the diagnosis of glaucoma based on deep learning, the blood vessels within the...

Deep learning architecture with shunted transformer and 3D deformable convolution for voxel-level dose prediction of head and neck tumors.

Physical and engineering sciences in medicine
Intensity-modulated radiation therapy (IMRT) has been widely used in treating head and neck tumors. However, due to the complex anatomical structures in the head and neck region, it is challenging for the plan optimizer to rapidly generate clinically...

Optimal STI controls for HIV patients based on an efficient deep Q learning method.

Journal of theoretical biology
We investigate an efficient computational tool to suggest useful treatment regimens for people infected with the human immunodeficiency virus (HIV). Structured treatment interruption (STI) is a regimen in which therapeutic drugs are periodically admi...

Boosting the performance of molecular property prediction via graph-text alignment and multi-granularity representation enhancement.

Journal of molecular graphics & modelling
Deep learning is playing an increasingly important role in accurate prediction of molecular properties. Prior to being processed by a deep learning model, a molecule is typically represented in the form of a text or a graph. While some methods attemp...

An attribution graph-based interpretable method for CNNs.

Neural networks : the official journal of the International Neural Network Society
Convolutional Neural Networks (CNNs) have demonstrated outstanding performance in various domains, such as face recognition, object detection, and image segmentation. However, the lack of transparency and limited interpretability inherent in CNNs pos...

Human-robot interaction in motor imagery: A system based on the STFCN for unilateral upper limb rehabilitation assistance.

Journal of neuroscience methods
BACKGROUND: Rehabilitation training based on the brain-computer interface of motor imagery (MI-BCI) can help restore the connection between the brain and movement. However, the performance of most popular MI-BCI system is coarse-level, which means th...

Nanoscale single-vesicle analysis: High-throughput approaches through AI-enhanced super-resolution image analysis.

Biosensors & bioelectronics
The analysis of membrane vesicles at the nanoscale level is crucial for advancing the understanding of intercellular communication and its implications for health and disease. Despite their significance, the nanoscale analysis of vesicles at the sing...