AIMC Topic: Young Adult

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Judges versus artificial intelligence in juror decision-making in criminal trials: Evidence from two pre-registered experiments.

PloS one
BACKGROUND: Artificial intelligence (AI) is anticipated to play a significant role in criminal trials involving citizen jurors. Prior studies have suggested that AI is not widely preferred in ethical decision-making contexts, but little research has ...

The effect of empathy on remote social connections via paired robots.

PloS one
A range of devices and technologies are available to mediate social connections between geographically distant people. Some of these methods exploit awareness information to enhance the connectedness of distant users. However, the effect of user trai...

Phase-contrast magnetic resonance imaging-based predictive modelling for surgical outcomes in patients with Chiari malformation type 1 with syringomyelia: a machine learning study.

Clinical radiology
AIM: Prospective outcome prediction plays a crucial role in guiding preoperative decision-making in patients with Chiari malformation type I (CM-Ⅰ) with syringomyelia. Here, we aimed to develop a predictive model for postoperative outcomes in patient...

Decision tree-based learning and laboratory data mining: an efficient approach to amebiasis testing.

Parasites & vectors
BACKGROUND: Amebiasis represents a significant global health concern. This is especially evident in developing countries, where infections are more common. The primary diagnostic method in laboratories involves the microscopy of stool samples. Howeve...

An Explainable Artificial Intelligence Text Classifier for Suicidality Prediction in Youth Crisis Text Line Users: Development and Validation Study.

JMIR public health and surveillance
BACKGROUND: Suicide represents a critical public health concern, and machine learning (ML) models offer the potential for identifying at-risk individuals. Recent studies using benchmark datasets and real-world social media data have demonstrated the ...

Estimating the Prevalence of Schizophrenia in the General Population of Japan Using an Artificial Neural Network-Based Schizophrenia Classifier: Web-Based Cross-Sectional Survey.

JMIR formative research
BACKGROUND: Estimating the prevalence of schizophrenia in the general population remains a challenge worldwide, as well as in Japan. Few studies have estimated schizophrenia prevalence in the Japanese population and have often relied on reports from ...

Intraindividual Comparison of Image Quality Between Low-Dose and Ultra-Low-Dose Abdominal CT With Deep Learning Reconstruction and Standard-Dose Abdominal CT Using Dual-Split Scan.

Investigative radiology
OBJECTIVE: The aim of this study was to intraindividually compare the conspicuity of focal liver lesions (FLLs) between low- and ultra-low-dose computed tomography (CT) with deep learning reconstruction (DLR) and standard-dose CT with model-based ite...

3D face reconstruction for maxillofacial surgery based on morphable models and neural networks: A preliminary assessment for anthropometry accuracy.

Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery
OBJECTIVES: This study aimed to evaluate the anthropometric accuracy of 3D face reconstruction based on neural networks (3DFRBN) using 2D images, including the assessment of global errors and landmarks, as well as linear and angular measurements.

Deep learning based tractography with TractSeg in patients with hemispherotomy: Evaluation and refinement.

NeuroImage. Clinical
Deep learning-based tractography implicitly learns anatomical prior knowledge that is required to resolve ambiguities inherent in traditional streamline tractography. TractSeg is a particularly widely used example of such an approach. Even though it ...

A novel clinical investigation using deep learning and human-in-the-loop approach in orbital volume measurement.

Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery
Orbital volume assessment is crucial for surgical planning. Traditional methods lack efficiency and accuracy. Recent studies explore AI-driven techniques, but research on their clinical effectiveness is limited. This study included 349 patients aged ...