AIMC Topic: Deep Learning

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Evaluating the ecological vulnerability of Chongqing using deep learning.

Environmental science and pollution research international
This study used deep learning to evaluate the ecological vulnerability of Chongqing, China, discuss the deep learning evaluations of ecological vulnerability, and generate vulnerability maps that support local ecological environment protection and go...

A Probabilistic Digital Twin for Leak Localization in Water Distribution Networks Using Generative Deep Learning.

Sensors (Basel, Switzerland)
Localizing leakages in large water distribution systems is an important and ever-present problem. Due to the complexity originating from water pipeline networks, too few sensors, and noisy measurements, this is a highly challenging problem to solve. ...

High accuracy epidermal growth factor receptor mutation prediction via histopathological deep learning.

BMC pulmonary medicine
BACKGROUND: The detection of epidermal growth factor receptor (EGFR) mutations in patients with non-small cell lung cancer is critical for tyrosine kinase inhibitor therapy. EGFR detection requires tissue samples, which are difficult to obtain in som...

Multimodal deep learning for COVID-19 prognosis prediction in the emergency department: a bi-centric study.

Scientific reports
Predicting clinical deterioration in COVID-19 patients remains a challenging task in the Emergency Department (ED). To address this aim, we developed an artificial neural network using textual (e.g. patient history) and tabular (e.g. laboratory value...

Deep Learning-Assisted Gait Parameter Assessment for Neurodegenerative Diseases: Model Development and Validation.

Journal of medical Internet research
BACKGROUND: Neurodegenerative diseases (NDDs) are prevalent among older adults worldwide. Early diagnosis of NDD is challenging yet crucial. Gait status has been identified as an indicator of early-stage NDD changes and can play a significant role in...

Magnetic Resonance Spectroscopy Spectral Registration Using Deep Learning.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Deep learning-based methods have been successfully applied to MRI image registration. However, there is a lack of deep learning-based registration methods for magnetic resonance spectroscopy (MRS) spectral registration (SR).

Au-Ag OHCs-based SERS sensor coupled with deep learning CNN algorithm to quantify thiram and pymetrozine in tea.

Food chemistry
Pesticide residue detection in food has become increasingly important. Herein, surface-enhanced Raman scattering (SERS) coupled with an intelligent algorithm was developed for the rapid and sensitive detection of pesticide residues in tea. By employi...

Recent advances in artificial intelligence for cardiac CT: Enhancing diagnosis and prognosis prediction.

Diagnostic and interventional imaging
Recent advances in artificial intelligence (AI) for cardiac computed tomography (CT) have shown great potential in enhancing diagnosis and prognosis prediction in patients with cardiovascular disease. Deep learning, a type of machine learning, has re...

Examining the effectiveness of a deep learning-based computer-aided breast cancer detection system for breast ultrasound.

Journal of medical ultrasonics (2001)
PURPOSE: This study aimed to evaluate the clinical usefulness of a deep learning-based computer-aided detection (CADe) system for breast ultrasound.

Clinical target volume delineation quality assurance for MRI-guided prostate radiotherapy using deep learning with uncertainty estimation.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Previous studies on automatic delineation quality assurance (QA) have mostly focused on CT-based planning. As MRI-guided radiotherapy is increasingly utilized in prostate cancer treatment, there is a need for more research on ...