Latest AI and machine learning research in anxiety & stress for healthcare professionals.
Advances in automated and high-throughput imaging technologies have resulted in a deluge of high-resolution images and sensor data of plants. However, extracting patterns and features from this large corpus of data requires the use of machine learning (ML) tools to enable data assimilation and feature identification for stress phenotyping. Four stages of the decision cycle in plant stress phenotyp...
Numerous studies have suggested that neuronal cells are protected against oxidative stress-induced cell damage by antioxidants, such as polyphenolic compounds. Phellinus linteus (PL) has traditionally been used to treat various symptoms in East Asian countries. In the present study, we prepared an ethyl acetate extract from the fruiting bodies of PL (PLEA) using hot water extraction, ethanol preci...
An accurate and noninvasive stress assessment from human physiology is a strenuous task. In this paper, a pattern recognition system to learn complex ...
BACKGROUND: Pre-deployment identification of soldiers at risk for long-term posttraumatic stress psychopathology after home coming is important to gui...
Although decades of efforts have been spent studying the pathogenesis of social anxiety disorder (SAD), there are still no objective biological marker...
Roots play an immediate role as the interface for water acquisition. To improve sustainability in low-water environments, breeders of major crops must...
A sensitive, stability-indicating, gradient reversed-phase ultra-performance liquid chromatography method has been developed for the quantitative esti...
OBJECTIVE: The continual increase in production and disposal of nanomaterials raises concerns regarding the safety of nanoparticles on the environment...
Cognitive behavior therapy (CBT) is an effective treatment for social anxiety disorder (SAD), but many patients do not respond sufficiently and a subs...
While neuroimaging research has advanced our knowledge about fear circuitry dysfunctions in anxiety disorders, findings based on diagnostic groups do ...
Background: Cognitive behavioural therapy (CBT) is the most frequently used and recommended therapy program for mental health conditions, including fo...
Early and accurate detection of crop stress is essential to improve agricultural productivity and ensure global food security. However, collecting a l...
Background: Apical sparing of left ventricular longitudinal strain (LS) is an echocardiographic clue to cardiac amyloidosis but may also occur in hype...
Explainable machine learning (XML) pipelines applied to composite mental health outcomes can produce apparently-robust, cross-population-stable risk h...
Cell states are increasingly conceptualized as attractors of high-dimensional dynamical systems, yet quantitative approaches for integrating phenotypi...
Accurate prediction of stress and strain fields in hierarchical composite microstructures is critical for physics-informed material design, yet conven...
Depression and anxiety are highly prevalent in multiple sclerosis (MS), yet tools for predicting mental health trajectories from clinical data remain ...
Anxiety has been linked to difficulty sustaining engagement with ongoing tasks, even when continued engagement would yield greater rewards, yet the un...
Background: Suicide prediction models in psychiatry often rely on purely data-driven feature selection, which can produce unstable and clinically opaq...
Anxiety is associated with altered patterns of attention to images and objects, but how it influences the perception of continuous experiences remains...