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Correction: Multi-modal characterisation of early-stage, subclinical cardiac deterioration in patients with type 2 diabetes.
Cardiovasc Diabetol
January 2025
Computational Cardiovascular Science Group, Department of Computer Science, University of Oxford, Oxford, OX1 3QD, UK.
Syntalos: a software for precise synchronization of simultaneous multi-modal data acquisition and closed-loop interventions.
Nat Commun
January 2025
Institute of Physiology and Pathophysiology, Medical Faculty, Heidelberg University, Heidelberg, Germany.
Complex experimental protocols often require multi-modal data acquisition with precisely aligned timing, as well as state- and behavior-dependent interventions. Tailored solutions are mostly restricted to individual experimental setups and lack flexibility and interoperability. We present an open-source, Linux-based integrated software solution, called 'Syntalos', for simultaneous acquisition and synchronization of data from an arbitrary number of sources, including multi-channel electrophysiological recordings and different live imaging devices, as well as closed-loop, real-time interventions with different actuators.
View Article and Find Full Text PDFAboveground biomass estimation in a grassland ecosystem using Sentinel-2 satellite imagery and machine learning algorithms.
Environ Monit Assess
January 2025
School of Geography, Archaeology and Environmental Studies, University of the Witwatersrand, Johannesburg, 2000, South Africa.
The grassland ecosystem forms a critical part of the natural ecosystem, covering up to 15-26% of the Earth's land surface. Grassland significantly impacts the carbon cycle and climate regulation by storing carbon dioxide. The organic matter found in grassland biomass, which acts as a carbon source, greatly expands the carbon stock in terrestrial ecosystems.
View Article and Find Full Text PDFPredicting the diabetic foot in the population of type 2 diabetes mellitus from tongue images and clinical information using multi-modal deep learning.
Front Physiol
December 2024
School of Health Sciences and Engineering, Tianjin University of Traditional Chinese Medicine, Tianjin, China.
Aims: Based on the quantitative and qualitative fusion data of traditional Chinese medicine (TCM) and Western medicine, a diabetic foot (DF) prediction model was established through combining the objectified parameters of TCM and Western medicine.
Methods: The ResNet-50 deep neural network (DNN) was used to extract depth features of tongue demonstration, and then a fully connected layer (FCL) was used for feature extraction to obtain aggregate features. Finally, a non-invasive DF prediction model based on tongue features was realized.
Common sports-related nerve injuries seen by the electrodiagnostic medical consultant.
Muscle Nerve
November 2024
Department of Medicine, Division of Physical Medicine and Rehabilitation, University of Toronto, Toronto, Ontario, Canada.
The high physiologic demands of sports create dynamic stress on joints, soft tissues, and nerves which may lead to injuries in the athlete. Electrodiagnostic (EDx) assessment is essential to identify the correct diagnosis, localization, and prognosis, to guide management of sports-related neuropathies. A comprehensive review was performed to provide the EDx medical consultant with a practical approach to the common peripheral nerve disorders seen in athletes.
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