AIMC Topic: Young Adult

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Performance investigation of MVMD-MSI algorithm in frequency recognition for SSVEP-based brain-computer interface and its application in robotic arm control.

Medical & biological engineering & computing
This study focuses on improving the performance of steady-state visual evoked potential (SSVEP) in brain-computer interfaces (BCIs) for robotic control systems. The challenge lies in effectively reducing the impact of artifacts on raw data to enhance...

Multi-stain deep learning prediction model of treatment response in lupus nephritis based on renal histopathology.

Kidney international
The response of the kidney after induction treatment is one of the determinants of prognosis in lupus nephritis, but effective predictive tools are lacking. Here, we sought to apply deep learning approaches on kidney biopsies for treatment response p...

Evaluation of the effectiveness of panoramic radiography in impacted mandibular third molars on deep learning models developed with findings obtained with cone beam computed tomography.

Oral radiology
OBJECTIVE: The aim of this study is to determine the contact relationship and position of impacted mandibular third molar teeth (IMM) with the mandibular canal (MC) in panoramic radiography (PR) images using deep learning (DL) models trained with the...

Digital phenotyping from heart rate dynamics: Identification of zero-poles models with data-driven evolutionary learning.

Computers in biology and medicine
Heart rate response to physical activity is widely investigated in clinical and training practice, as it provides information on a person's physical state. For emerging digital phenotyping approaches, there is a need for individualized model estimati...

A novel way to use cross-validation to measure connectivity by machine learning allows epilepsy surgery outcome prediction.

NeuroImage
The rate of success of epilepsy surgery, ensuring seizure-freedom, is limited by the lack of epileptogenicity biomarkers. Previous evidence supports the critical role of functional connectivity during seizure generation to characterize the epileptoge...

Machine learning prediction model of the treatment response in schizophrenia reveals the importance of metabolic and subjective characteristics.

Schizophrenia research
Predicting early treatment response in schizophrenia is pivotal for selecting the best therapeutic approach. Utilizing machine learning (ML) technique, we aimed to formulate a model predicting antipsychotic treatment outcomes. Data were obtained from...

Developing and Improving Personality Inventories Using Generative Artificial Intelligence: The Psychometric Properties of a Short HEXACO Scale Developed Using ChatGPT 4.0.

Journal of personality assessment
In the current study, we investigated the utility of generative AI for survey development and improvement. To do so, we generated a 24-item HEXACO personality inventory using ChatGPT 4.0, the ChatGPT HEXACO inventory (CHI), and investigated whether C...

High specificity of an AI-powered framework in cross-checking male professional football anterior cruciate ligament tear reports in public databases.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: While public databases like Transfermarkt provide valuable data for assessing the impact of anterior cruciate ligament (ACL) injuries in professional footballers, they require robust verification methods due to accuracy concerns. We hypothes...

Identifying potential medical aid beneficiaries using machine learning: A Korean Nationwide cohort study.

International journal of medical informatics
OBJECTIVE: To identify potential medical aid beneficiaries using demographic and medical history of individuals and analyzing important features qualitatively.