AIMC Topic: Deep Learning

Clear Filters Showing 10311 to 10320 of 28423 articles

Deductive automated pollen classification in environmental samples via exploratory deep learning and imaging flow cytometry.

The New phytologist
Pollen and tracheophyte spores are ubiquitous environmental indicators at local and global scales. Palynology is typically performed manually by microscopic analysis; a specialised and time-consuming task limited in taxonomical precision and sampling...

A deep learning approach based on multi-omics data integration to construct a risk stratification prediction model for skin cutaneous melanoma.

Journal of cancer research and clinical oncology
PURPOSE: Skin cutaneous melanoma (SKCM) is a highly aggressive melanocytic carcinoma whose high heterogeneity and complex etiology make its prognosis difficult to predict. This study aimed to construct a risk subtype typing model for SKCM.

Use of Deep-Learning Assisted Assessment of Cardiac Parameters in Zebrafish to Discover Cyanidin Chloride as a Novel Keap1 Inhibitor Against Doxorubicin-Induced Cardiotoxicity.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Doxorubicin-induced cardiomyopathy (DIC) brings tough clinical challenges as well as continued demand in developing agents for adjuvant cardioprotective therapies. Here, a zebrafish phenotypic screening with deep-learning assisted multiplex cardiac f...

Blockchain-Powered Healthcare Systems: Enhancing Scalability and Security with Hybrid Deep Learning.

Sensors (Basel, Switzerland)
The rapid advancements in technology have paved the way for innovative solutions in the healthcare domain, aiming to improve scalability and security while enhancing patient care. This abstract introduces a cutting-edge approach, leveraging blockchai...

IRv2-Net: A Deep Learning Framework for Enhanced Polyp Segmentation Performance Integrating InceptionResNetV2 and UNet Architecture with Test Time Augmentation Techniques.

Sensors (Basel, Switzerland)
Colorectal polyps in the colon or rectum are precancerous growths that can lead to a more severe disease called colorectal cancer. Accurate segmentation of polyps using medical imaging data is essential for effective diagnosis. However, manual segmen...

3DSleepNet: A Multi-Channel Bio-Signal Based Sleep Stages Classification Method Using Deep Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
A novel multi-channel-based 3D convolutional neural network (3D-CNN) is proposed in this paper to classify sleep stages. Time domain features, frequency domain features, and time-frequency domain features are extracted from electroencephalography (EE...

Coronary computed tomography angiographic detection of in-stent restenosis via deep learning reconstruction: a feasibility study.

European radiology
OBJECTIVES: Evaluation of in-stent restenosis (ISR), especially for small stents, remains challenging during computed tomography (CT) angiography. We used deep learning reconstruction to quantify stent strut thickness and lumen vessel diameter at the...

Performance of deep learning for detection of chronic kidney disease from retinal fundus photographs: A systematic review and meta-analysis.

European journal of ophthalmology
OBJECTIVE: Deep learning has been used to detect chronic kidney disease (CKD) from retinal fundus photographs. We aim to evaluate the performance of deep learning for CKD detection.

Coupling synthetic and real-world data for a deep learning-based segmentation process of 4D flow MRI.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Phase contrast magnetic resonance imaging (4D flow MRI) is an imaging technique able to provide blood velocity in vivo and morphological information. This capability has been used to study mainly the hemodynamics of large ve...

Short-axis PET image quality improvement based on a uEXPLORER total-body PET system through deep learning.

European journal of nuclear medicine and molecular imaging
PURPOSE: The axial field of view (AFOV) of a positron emission tomography (PET) scanner greatly affects the quality of PET images. Although a total-body PET scanner (uEXPLORER) with a large AFOV is more sensitive, it is more expensive and difficult t...