Researchers report that the integration of machine learning and Internet of Things (IoT) technologies is enabling a new generation of intelligent industrial environments capable of real-time ...
Detecting behavioural signatures of depression from everyday digital traces is a central challenge in computational psychiatry. Real-world datasets from smartphones and wearables often suffer from ...
Abstract: To utilize water resources optimally, plan agricultural activities properly, and manage the risks of natural disasters in a country such as India where the economy relies heavily on the ...
It has long been known as the arbiter of reward in the brain, but recent findings could upend this classic theory of dopamine ...
Epilepsy is one of the common disorders known to man, with early accounts of the disorder traced back to antiquity.1 It was ...
This study, the first of its kind at the Issaka Gazoby maternity hospital in Niamey, highlighted several factors associated ...
Background Although the increased risk of cardiovascular disease in patients with SLE is well-documented, effective tools for risk stratification remain elusive. This study sought to explore the ...
Functional connectivity reveals brain attractors that match predictions of free‑energy‑minimizing attractor theory, yielding an interpretable generative model of brain dynamics in rest, task, and ...
Abstract: This paper presents a system for multivariate time series anomaly detection using deep learning, with an added module to reflect variable relationships. The system uses an autoencoder to ...
Background The presence of a coincident intracranial aneurysm (CIA) on the target vessel of patients undergoing mechanical thrombectomy (MT) for acute ischemic stroke (AIS) poses challenges, as the ...
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