AIMC Topic: Young Adult

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Which surrogate insulin resistance indices best predict coronary artery disease? A machine learning approach.

Cardiovascular diabetology
BACKGROUND: Various surrogate markers of insulin resistance have been developed, capable of predicting coronary artery disease (CAD) without the need to detect serum insulin. For accurate prediction, they depend only on glucose and lipid profiles, as...

A machine learning approach for differentiating bipolar disorder type II and borderline personality disorder using electroencephalography and cognitive abnormalities.

PloS one
This study addresses the challenge of differentiating between bipolar disorder II (BD II) and borderline personality disorder (BPD), which is complicated by overlapping symptoms. To overcome this, a multimodal machine learning approach was employed, ...

"How I would like AI used for my imaging": children and young persons' perspectives.

European radiology
OBJECTIVES: Artificial intelligence (AI) tools are becoming more available in modern healthcare, particularly in radiology, although less attention has been paid to applications for children and young people. In the development of these, it is critic...

Predictive analysis on the factors associated with birth Outcomes: A machine learning perspective.

International journal of medical informatics
BACKGROUND: Recent studies reveal that around 1.9 million stillbirths occur annually worldwide, with Sub-Saharan Africa having among the highest cases. Some Sub-Saharan African countries, including Ghana, failed to meet Millennium Development Goal 5 ...

Enhancing Breast Cancer Diagnosis: A Nomogram Model Integrating AI Ultrasound and Clinical Factors.

Ultrasound in medicine & biology
PURPOSE: A novel nomogram incorporating artificial intelligence (AI) and clinical features for enhanced ultrasound prediction of benign and malignant breast masses.

Machine learning predicts the serum PFOA and PFOS levels in pregnant women: Enhancement of fatty acid status on model performance.

Environment international
Human exposure to per- and polyfluoroalkyl substances (PFASs) has received considerable attention, particularly in pregnant women because of their dramatic changes in physiological status and dietary patterns. Predicting internal PFAS exposure in pre...

Self-Supervised Learning Improves Accuracy and Data Efficiency for IMU-Based Ground Reaction Force Estimation.

IEEE transactions on bio-medical engineering
OBJECTIVE: Recent deep learning techniques hold promise to enable IMU-driven kinetic assessment; however, they require large extents of ground reaction force (GRF) data to serve as labels for supervised model training. We thus propose using existing ...

TacPrint: Visualizing the Biomechanical Fingerprint in Table Tennis.

IEEE transactions on visualization and computer graphics
Table tennis is a sport that demands high levels of technical proficiency and body coordination from players. Biomechanical fingerprints can provide valuable insights into players' habitual movement patterns and characteristics, allowing them to iden...

Evaluation of future nurses' knowledge, attitudes and anxiety levels about artificial intelligence applications.

Journal of evaluation in clinical practice
RATIONALE: Evaluating future nurses' perspectives on artificial intelligence, determining their missing or incorrect information on the subject and determining their anxiety levels are of great importance in terms of providing science and technology-...

Aberrant patterns of spontaneous brain activity in schizophrenia: A resting-state fMRI study and classification analysis.

Progress in neuro-psychopharmacology & biological psychiatry
BACKGROUND: Schizophrenia is a prevalent mental disorder, leading to severe disability. Currently, the absence of objective biomarkers hinders effective diagnosis. This study was conducted to explore the aberrant spontaneous brain activity and invest...