AIMC Topic: Adult

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Mapping dental biofilms: from plaque index through planimetry to volumetric analysis.

Clinical oral investigations
OBJECTIVES: Conventional plaque assessment methods, such as clinical indices and planimetry, rely on plaque-disclosing agents and may overemphasize thin biofilm areas due to plaque thickness variations. This study introduces a digital 3D method to qu...

Evaluating AI chatbots in neurological function test interpretation for brain tumor surgery.

Neurosurgical review
Neuropsychological assessments are essential for evaluating functional status and guiding surgical planning in patients with brain tumors. However, their complexity may hinder interpretation for patients and junior clinicians. Large language model (L...

Understanding surgeon adoption of artificial intelligence surgical technology: integrating UTAUT-TOE model.

Journal of robotic surgery
Artificial intelligence (AI) has become a transformative technology in surgical practice, revolutionizing modern healthcare and offering advancements in precision, efficiency, and patient outcomes. Despite its potential, the integration of AI technol...

Contactless biometric verification from in-air signatures using deep siamese networks.

Scientific reports
In-air signature is a behavioral biometric trait that has gained increasing attention in recent years due to its contactless nature and potential for secure, hygienic, and remote authentication. Unlike traditional pen-and-paper or tablet-based system...

Factors associated with complication of cranioplasty: CT-based risk assessment for early failure of autologous-bone cranioplasty.

Neurosurgical review
To determine whether preoperative noncontrast CT features predict early revision after autologous bone cranioplasty and to develop a simple CT-based risk framework. We retrospectively studied adults undergoing autologous cranioplasty at a single cent...

Construction and temporal external validation of interpretable machine-learning models for predicting tigecycline-associated hypofibrinogenemia.

European journal of clinical pharmacology
BACKGROUND AND PURPOSE: There is a paucity of available clinical tools with which to accurately predict the risk of tigecycline-associated hypofibrinogenemia, an adverse reaction with a high incidence and serious consequences. This study aimed to dev...

Stress detection using the phase controlled Bi-channel adaptive features from the brain EEG signals.

Computers in biology and medicine
This work proposes a stress classification system from the electroencephalogram (EEG) signals collected from the stress subjects. The scheme extracts the phase-controlled Bi-channel adaptive features using a pair of EEG signals. The proposed adaptive...

What Drives Microplastic Exposure in Human Blood and Feces? Machine Learning Reveals Potential Key Influencing Factors.

Environmental science & technology
Microplastics are pervasive environmental pollutants, making human exposure unavoidable. Although previous studies have detected microplastics in human blood and feces, these investigations were limited by small sample sizes and key contributors to m...

How perceived stress and social support shape non-communicable disease risks beyond traditional factors: a machine learning perspective.

BMC public health
BACKGROUND: Psychosocial factors such as perceived stress and social support have been increasingly recognized as significant contributors to non-communicable diseases (NCDs). However, their predictive value in comparison to traditional risk factors ...

Predicting Ultra-High Risk Outcomes Using Linguistic and Acoustic Measures From High-Risk Social Challenge Recordings: mHealth Longitudinal Cohort Exploratory Study.

JMIR formative research
BACKGROUND: Early detection of individuals at ultra-high risk (UHR) for psychosis is critical for timely intervention and improving clinical outcomes. However, current UHR assessments, which rely heavily on psychometric tools, often suffer from low s...