AIMC Topic: Young Adult

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Estimation of human age using machine learning on panoramic radiographs for Brazilian patients.

Scientific reports
This paper addresses a relevant problem in Forensic Sciences by integrating radiological techniques with advanced machine learning methodologies to create a non-invasive, efficient, and less examiner-dependent approach to age estimation. Our study in...

Influence of a robotic companion on women's food choices: Evidence from an imaginary task.

Applied psychology. Health and well-being
Previous research has demonstrated the influence of commensal dining between humans on food choices, whereas we conducted two studies to examine how the presence of a robot might influence people's choices between meat-heavy and vegetable-forward mea...

Predicting high blood pressure using machine learning models in low- and middle-income countries.

BMC medical informatics and decision making
Responding to the rising global prevalence of noncommunicable diseases (NCDs) requires improvements in the management of high blood pressure. Therefore, this study aims to develop an explainable machine learning model for predicting high blood pressu...

Factors for increasing positive predictive value of pneumothorax detection on chest radiographs using artificial intelligence.

Scientific reports
This study evaluated the positive predictive value (PPV) of artificial intelligence (AI) in detecting pneumothorax on chest radiographs (CXRs) and its affecting factors. Patients determined to have pneumothorax on CXR by a commercial AI software from...

Evaluation of perceived urgency from single-trial EEG data elicited by upper-body vibration feedback using deep learning.

Scientific reports
Notification systems that convey urgency without adding cognitive burden are crucial in human-computer interaction. Haptic feedback systems, particularly those utilizing vibration feedback, have emerged as a compelling solution, capable of providing ...

Impact of Emerging Deep Learning-Based MR Image Reconstruction Algorithms on Abdominal MRI Radiomic Features.

Journal of computer assisted tomography
OBJECTIVE: This study aims to evaluate, on one MRI vendor's platform, the impact of deep learning (DL)-based reconstruction techniques on MRI radiomic features compared to conventional image reconstruction techniques.

Assessing Axillary Lymph Node Burden and Prognosis in cT1-T2 Stage Breast Cancer Using Machine Learning Methods: A Retrospective Dual-Institutional MRI Study.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Pathological axillary lymph node (pALN) burden is an important factor for treatment decision-making in clinical T1-T2 (cT1-T2) stage breast cancer. Preoperative assessment of the pALN burden and prognosis aids in the individualized select...

Development of an equation to predict delta bilirubin levels using machine learning.

Clinica chimica acta; international journal of clinical chemistry
OBJECTIVE: Delta bilirubin (albumin-covalently bound bilirubin) may provide important clinical utility in identifying impaired hepatic excretion of conjugated bilirubin, but it cannot be measured in real-time for diagnostic purposes in clinical labor...

Investigating the role of artificial intelligence in predicting perceived dysphonia level.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
PURPOSE: This study aims to investigate the role of one of these models in the field of voice pathology and compare its performance in distinguishing the perceived dysphonia level.

Separating group- and individual-level brain signatures in the newborn functional connectome: A deep learning approach.

NeuroImage
Recent studies indicate that differences in cognition among individuals may be partially attributed to unique brain wiring patterns. While functional connectivity (FC)-based fingerprinting has demonstrated high accuracy in identifying adults, early s...