AIMC Topic: Deep Learning

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Deep Learning-Enhanced Hand-Driven Microfluidic Chip for Multiplexed Nucleic Acid Detection Based on RPA/CRISPR.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
The early detection of high-risk human papillomavirus (HR-HPV) is crucial for the assessment and improvement of prognosis in cervical cancer. However, existing PCR-based screening methods suffer from inadequate accessibility, which dampens the enthus...

A Physics-Integrated Deep Learning Approach for Patient-Specific Non-Newtonian Blood Viscosity Assessment using PPG.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The aim of this study is to extract a patient-specific viscosity equation from photoplethysmography (PPG) data. An aging society has increased the need for remote, non-invasive health monitoring systems. However, the circula...

Skin Cancer Detection Using Deep Learning Approaches.

Cancer biotherapy & radiopharmaceuticals
This review examined multiple deep learning (DL) methods, including artificial neural networks (ANNs), convolutional neural networks (CNNs), k-nearest neighbors (KNNs), as well as generative adversarial networks (GANs), relying on their abilities to...

CR-deal: Explainable Neural Network for circRNA-RBP Binding Site Recognition and Interpretation.

Interdisciplinary sciences, computational life sciences
circRNAs are a type of single-stranded non-coding RNA molecules, and their unique feature is their closed circular structure. The interaction between circRNAs and RNA-binding proteins (RBPs) plays a key role in biological functions and is crucial for...

Using deep-learning based segmentation to enable spatial evaluation of knee osteoarthritis (SEKO) in rodent models.

Osteoarthritis and cartilage
OBJECTIVE: In preclinical models of osteoarthritis (OA), histology is commonly used to evaluate joint remodeling. The current study introduces a deep learning driven histological analysis pipeline for the spatial evaluation of knee osteoarthritis (SE...

Deep learning based on ultrasound images predicting cervical lymph node metastasis in postoperative patients with differentiated thyroid carcinoma.

The British journal of radiology
OBJECTIVES: To develop a deep learning (DL) model based on ultrasound (US) images of lymph nodes for predicting cervical lymph node metastasis (CLNM) in postoperative patients with differentiated thyroid carcinoma (DTC).

Fast Virtual Stenting for Thoracic Endovascular Aortic Repair of Aortic Dissection Using Graph Deep Learning.

IEEE journal of biomedical and health informatics
Fast virtual stenting (FVS) is a promising preoperative planning aid for thoracic endovascular aortic repair (TEVAR) of aortic dissection. It aims at digitally predicting the reshaped aortic true lumen (TL) under specific operation plans (stent-graft...

Predicting Mutation-Disease Associations Through Protein Interactions Via Deep Learning.

IEEE journal of biomedical and health informatics
Disease is one of the primary factors affecting life activities, with complex etiologies often influenced by gene expression and mutation. Currently, wet lab experiments have analyzed the mechanisms of mutations, but these are usually limited by the ...

Ultra-Sparse-View Cone-Beam CT Reconstruction-Based Strictly Structure-Preserved Deep Neural Network in Image-Guided Radiation Therapy.

IEEE transactions on medical imaging
Radiation therapy is regarded as the mainstay treatment for cancer in clinic. Kilovoltage cone-beam CT (CBCT) images have been acquired for most treatment sites as the clinical routine for image-guided radiation therapy (IGRT). However, repeated CBCT...