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Attentional responses in toddlers: A protocol for assessing the impact of a robotic animated animal and a real dog.

PloS one
BACKGROUND: Attentional processes in toddlers are characterized by a state of alertness in which they focus their waking state for short periods. It is essential to develop assessment and attention stimulation protocols from an early age to improve t...

Understanding dimensions of trust in AI through quantitative cognition: Implications for human-AI collaboration.

PloS one
Human-AI collaborative innovation relies on effective and clearly defined role allocation, yet empirical research in this area remains limited. To address this gap, we construct a cognitive taxonomy trust in AI framework to describe and explain its i...

MRI based early Temporal Lobe Epilepsy detection using DGWO based optimized HAETN and Fuzzy-AAL Segmentation Framework (FASF).

PloS one
This work aims to promote early and accurate diagnosis of Temporal Lobe Epilepsy (TLE) by developing state-of-the-art deep learning techniques, with the goal of minimizing the consequences of epilepsy on individuals and society. Current approaches fo...

Educational improvement through machine learning: Strategic models for better PISA scores.

PloS one
In this study, in addition to traditional variables such as economic wealth or the number of books read, on which many studies have already been conducted, variables that are thought to influence student achievement and better predict success are ide...

Iron metabolism and preeclampsia: new insights from bioinformatics analysis.

The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians
OBJECTIVE: Preeclampsia (PE) is a multifactorial systemic pregnancy disease, in which iron metabolism and ferroptosis play significant roles during its pathogenesis. The diagnosis and prevention of PE remain urgent clinical issues that need to be add...

Development and validation of peripheral blood DNA methylation signatures to predict response to biological therapy in adults with Crohn's disease (EPIC-CD): an epigenome-wide association study.

The lancet. Gastroenterology & hepatology
BACKGROUND: Biological therapeutics are widely used in Crohn's disease, with evidence of efficacy from randomised trials and real-world experience. Primary non-response is a common, poorly understood problem. We aimed to assess blood methylation as a...

Multiomic based Bayesian network toxicity modeling for simultaneous prediction of multiple toxicity outcomes in NSCLC.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE: Radiation Pneumonitis (RP) and Radiation Esophagitis (RE) are two prominent dose limiting toxicities from NSCLC radiotherapy. This study aimed to develop a multi-objective Bayesian network (BN) model to predict multiple NSCLC outcomes simult...

Improving YOLO-based breast mass detection with transfer learning pretraining on the OPTIMAM Mammography Image Database.

Computers in biology and medicine
BACKGROUND AND OBJECTIVES: Early detection of breast cancer through mammography significantly improves survival rates. However, high false positive and false negative rates remain a challenge. Deep learning-based computer-aided diagnosis systems can ...

The General Attitudes towards Artificial Intelligence Scale (GAAIS): validation and psychometric properties analysis in the Italian context.

BMC psychology
This two-study investigation aimed to assess the psychometric properties of the Italian version of the General Attitudes towards Artificial Intelligence Scale (GAAIS). In study 1 (N = 236 adults) confirmatory factor analysis (CFA) was conducted to ex...