AIMC Topic: Deep Learning

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Deep learning-based total suspended solids concentration classification of stream water surface images captured by mobile phone.

Environmental monitoring and assessment
The continuous monitoring of total suspended solids (TSS) in streams plays an important role in the management of hydrological processes, and TSS is also a decisive parameter in the control of pollution in streams. Determination of TSS involves both ...

Real-time counting of wheezing events from lung sounds using deep learning algorithms: Implications for disease prediction and early intervention.

PloS one
This pioneering study aims to revolutionize self-symptom management and telemedicine-based remote monitoring through the development of a real-time wheeze counting algorithm. Leveraging a novel approach that includes the detailed labeling of one brea...

FiCRoN, a deep learning-based algorithm for the automatic determination of intracellular parasite burden from fluorescence microscopy images.

Medical image analysis
Protozoan parasites are responsible for dramatic, neglected diseases. The automatic determination of intracellular parasite burden from fluorescence microscopy images is a challenging problem. Recent advances in deep learning are transforming this pr...

An attention 3DUNET and visual geometry group-19 based deep neural network for brain tumor segmentation and classification from MRI.

Journal of biomolecular structure & dynamics
There has been an abrupt increase in brain tumor (BT) related medical cases during the past ten years. The tenth most typical type of tumor affecting millions of people is the BT. The cure rate can, however, rise if it is found early. When evaluating...

A spatio-temporal deep learning approach to simulating conflict risk propagation on freeways with trajectory data.

Accident; analysis and prevention
On freeways, sudden deceleration or lane-changing by vehicles can trigger conflict risk that propagates backward in a specific pattern. Simulating this pattern of conflict risk propagation can not only help prevent crashes but is also vital for the d...

PET/CT based cross-modal deep learning signature to predict occult nodal metastasis in lung cancer.

Nature communications
Occult nodal metastasis (ONM) plays a significant role in comprehensive treatments of non-small cell lung cancer (NSCLC). This study aims to develop a deep learning signature based on positron emission tomography/computed tomography to predict ONM of...

Explainable deep learning for tumor dynamic modeling and overall survival prediction using Neural-ODE.

NPJ systems biology and applications
While tumor dynamic modeling has been widely applied to support the development of oncology drugs, there remains a need to increase predictivity, enable personalized therapy, and improve decision-making. We propose the use of Tumor Dynamic Neural-ODE...

Ultra-High-Resolution T2-Weighted PROPELLER MRI of the Rectum With Deep Learning Reconstruction: Assessment of Image Quality and Diagnostic Performance.

Investigative radiology
OBJECTIVE: The aim of this study was to evaluate the impact of ultra-high-resolution acquisition and deep learning reconstruction (DLR) on the image quality and diagnostic performance of T2-weighted periodically rotated overlapping parallel lines wit...

Deep learning enhanced multiplex detection of viable foodborne pathogens in digital microfluidic chip.

Biosensors & bioelectronics
Culture plating is worldwide accepted as the gold standard for quantifying viable foodborne pathogens. However, it is time-consuming (1-2 days) and requires specialized laboratory and personnel. This study reported a deep learning enhanced digital mi...