Psychiatry

A Case Study of Multiple Maintenance Efficacy in Gynaecological Surgery Assessed by Deep Learning.

Deep learning is a new learning concept and a highly effective way of learning, which is still being explored in the field of nursing education. This paper analyses the effectiveness of interventions in perioperative gynaecological care using humanised care in the operating theatre and the impact of this model of care on patients' psychological well-being and sleep quality. A deep learning-based v...

Explaining Aha! moments in artificial agents through IKE-XAI: Implicit Knowledge Extraction for eXplainable AI.

During the learning process, a child develops a mental representation of the task he or she is learning. A Machine Learning algorithm develops also a latent representation of the task it learns. We investigate the development of the knowledge construction of an artificial agent through the analysis of its behavior, i.e., its sequences of moves while learning to perform the Tower of Hanoï (TOH) tas...

Value-free random exploration is linked to impulsivity.

Deciding whether to forgo a good choice in favour of exploring a potentially more rewarding alternative is one of the most challenging arbitrations bo...

Deconstruction of physical fitness assessment system and medical rehabilitation countermeasures for physically disabled teenagers with natural language processing technology.

Disability is a component of social relations and the existence of social reality. An effective solution to the problem of persons with disabilities i...

AsthmaKGxE: An asthma-environment interaction knowledge graph leveraging public databases and scientific literature.

MOTIVATION: Asthma is a complex heterogeneous disease resulting from intricate interactions between genetic and non-genetic factors related to environ...

Controlled Growth of Wafer-Scale Transition Metal Dichalcogenides with a Vertical Composition Gradient for Artificial Synapses with High Linearity.

Artificial synapses are promising for dealing with large amounts of data computing. Great progress has been made recently in terms of improving the on...

Sweat Proteomics in Cystic Fibrosis: Discovering Companion Biomarkers for Precision Medicine and Therapeutic Development.

In clinical routine, the diagnosis of cystic fibrosis (CF) is still challenging regardless of international consensus on diagnosis guidelines and test...

Language-agnostic deep learning framework for automatic monitoring of population-level mental health from social networks.

In many countries, mental health issues are among the most serious public health concerns. National mental health statistics are frequently collected ...

Sex differences in rTMS treatment response: A deep learning-based EEG investigation.

INTRODUCTION: The present study aimed to investigate sex differences in response to repetitive transcranial magnetic stimulation (rTMS) in Major Depre...

Predictors of accurate intrapedicular screw placement in single-level lumbar (L4-5) fusion: robot-assisted pedicle screw, traditional pedicle screw, and cortical bone trajectory screw insertion.

BACKGROUND: The superiorities in proximal facet joint protection of robot-assisted (RA) pedicle screw placement and screw implantation via the cortica...

Four-Class Classification of Neuropsychiatric Disorders by Use of Functional Near-Infrared Spectroscopy Derived Biomarkers.

Diagnosis of most neuropsychiatric disorders relies on subjective measures, which makes the reliability of final clinical decisions questionable. The ...

Aberrated Multidimensional EEG Characteristics in Patients with Generalized Anxiety Disorder: A Machine-Learning Based Analysis Framework.

Although increasing evidences support the notion that psychiatric disorders are associated with abnormal communication between brain regions, scattere...

Monopolar, bipolar, tripolar, and tetrapolar configurations in robot assisted electrical impedance sensing.

Tissue recognition is a critical process during a Robot-assisted minimally invasive surgery (RMIS) and it relies on the involvement of advanced sensin...

Online music-assisted rehabilitation system for depressed people based on deep learning.

The processing of negative emotions is closely related to the occurrence of depression, and improving the mood of patients with depression has an impo...

IGBT Fault Prediction Combining Terminal Characteristics and Artificial Intelligence Neural Network.

The insulated gate bipolar transistor (IGBT) is widely utilized in the transportation, power, and energy domains because of its high input impedance a...

Barriers to Use Artificial Intelligence Methodologies in Health Technology Assessment in Central and East European Countries.

The aim of this paper is to identify the barriers that are specifically relevant to the use of Artificial Intelligence (AI)-based evidence in Central ...

Exploring COVID-19-Related Stressors: Topic Modeling Study.

BACKGROUND: The COVID-19 pandemic has affected the lives of people globally for over 2 years. Changes in lifestyles due to the pandemic may cause psyc...

Artificial intelligence and machine-learning approaches in structure and ligand-based discovery of drugs affecting central nervous system.

CNS disorders are indications with a very high unmet medical needs, relatively smaller number of available drugs, and a subpar satisfaction level amon...

Otisma: an integrated application and humanoid robot as an educational tool for children with autism.

Autistic children have difficulty communicating wants, needs, and thoughts. In cases of low functioning autism, an individual can have serious speech ...

EEG based depression recognition using improved graph convolutional neural network.

Depression is a global psychological disease that does serious harm to people. Traditional diagnostic method of the doctor-patient communication, is n...