AIMC Topic: Deep Learning

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Improved Surface Electromyogram-Based Hand-Wrist Force Estimation Using Deep Neural Networks and Cross-Joint Transfer Learning.

Sensors (Basel, Switzerland)
Deep neural networks (DNNs) and transfer learning (TL) have been used to improve surface electromyogram (sEMG)-based force estimation. However, prior studies focused mostly on applying TL within one joint, which limits dataset size and diversity. Her...

Clinically Significant Prostate Cancer Prediction Using Multimodal Deep Learning with Prostate-Specific Antigen Restriction.

Current oncology (Toronto, Ont.)
Prostate cancer (PCa) is a clinically heterogeneous disease. Predicting clinically significant PCa with low-intermediate prostate-specific antigen (PSA), which often includes aggressive cancers, is imperative. This study evaluated the predictive accu...

Integrating deep learning for visual question answering in Agricultural Disease Diagnostics: Case Study of Wheat Rust.

Scientific reports
This paper presents a novel approach to agricultural disease diagnostics through the integration of Deep Learning (DL) techniques with Visual Question Answering (VQA) systems, specifically targeting the detection of wheat rust. Wheat rust is a pervas...

Optimized robust learning framework based on big data for forecasting cardiovascular crises.

Scientific reports
Numerous Deep Learning (DL) scenarios have been developed for evolving new healthcare systems that leverage large datasets, distributed computing, and the Internet of Things (IoT). However, the data used in these scenarios tend to be noisy, necessita...

Topographic and quantitative correlation of structure and function using deep learning in subclinical biomarkers of intermediate age-related macular degeneration.

Scientific reports
To examine the morphological impact of deep learning (DL)-quantified biomarkers on point-wise sensitivity (PWS) using microperimetry (MP) and optical coherence tomography (OCT) in intermediate AMD (iAMD). Patients with iAMD were examined by OCT (Spec...

MIMIC-BP: A curated dataset for blood pressure estimation.

Scientific data
Blood pressure (BP) is one of the most prominent indicators of potential cardiovascular disorders. Traditionally, BP measurement relies on inflatable cuffs, which is inconvenient and limit the acquisition of such important health-related information ...

MaskDGNets: Masked-attention guided dynamic graph aggregation network for event extraction.

PloS one
Considering that the traditional deep learning event extraction method ignores the correlation between word features and sequence information, it cannot fully explore the hidden associations between events and events and between events and primary at...

Contrast-enhanced thin-slice abdominal CT with super-resolution deep learning reconstruction technique: evaluation of image quality and visibility of anatomical structures.

Japanese journal of radiology
PURPOSE: To compare image quality and visibility of anatomical structures on contrast-enhanced thin-slice abdominal CT images reconstructed using super-resolution deep learning reconstruction (SR-DLR), deep learning-based reconstruction (DLR), and hy...

Artificial intelligence and stroke imaging.

Current opinion in neurology
PURPOSE OF REVIEW: Though simple in its fundamental mechanism - a critical disruption of local blood supply - stroke is complicated by the intricate nature of the neural substrate, the neurovascular architecture, and their complex interactions in gen...

TV-Net: Temporal-Variable feature harmonizing Network for multivariate time series classification and interpretation.

Neural networks : the official journal of the International Neural Network Society
Multivariate time series classification (MTSC), which identifies categories of multiple sensor signals recorded in continuous time, is widely used in various fields such as transportation, finance, and medical treatment. The focused challenge remains...