AIMC Topic: Adult

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[Formula: see text] : explainable attentive transformers for identifying the factors influencing dental visits to enhance dental data completeness.

BMC oral health
BACKGROUND: Access to routine dental care is a cornerstone of preventive healthcare. Regular dental check-ups, which include professional cleanings, examinations, and preventive treatments, play a crucial role in preventing advanced dental diseases s...

Mixture of checkpoint experts for explainable seizure detection using wearable devices.

Scientific reports
The current gold standard for detecting epileptic seizures is in-hospital video-Electroencephalography (vEEG), but vEEG is resource-intensive and imposes considerable burdens on patients and caregivers. Wearable devices offer an alternative to monito...

Muscle synergy-driven ensemble learning framework for individualized stroke gait rehabilitation.

Scientific reports
This study proposes a novel ensemble machine learning (ML) framework integrating neurophysiological principles from muscle synergy analysis to support clinical decisions in stroke gait rehabilitation. The framework leverages spatial and temporal feat...

Enhancing Parenting Using AI: Exploratory Hackathon.

JMIR formative research
BACKGROUND: Parenting skills programs are the primary intervention for conduct disorders in children. The Pause app enhances these programs by providing digital microinterventions that reinforce learning between sessions and after program completion....

Machine learning-based prediction of stone-free status following extracorporeal shock wave lithotripsy.

World journal of urology
PURPOSE: To develop a machine learning model for predicting stone-free (SF) outcomes following extracorporeal shock wave lithotripsy (SWL) and to identify key clinical and stone-related predictors using interpretable machine learning techniques.

Real-world evaluation of the accuracy of the Viz.AI automated intracranial hemorrhage volume calculation tool.

Journal of neurointerventional surgery
BACKGROUND: Appropriate management of spontaneous intracerebral hemorrhage (ICH) and intraventricular hemorrhage (IVH) requires rapid, accurate volume estimation. Viz.AI has developed an artificial intelligence (AI)-powered ICH calculation tool that ...

Age-dependent effects of surgical approach in T3b differentiated thyroid carcinoma: a population-based analysis using machine learning.

Endocrine-related cancer
Current guidelines recommend total thyroidectomy for all T3b differentiated thyroid carcinoma (DTC) with gross strap muscle invasion, yet evidence supporting this universal approach remains limited and conflicting. We analyzed 6,920 T3b DTC patients ...

Identifying daily-living features related to loneliness: A causal machine learning approach.

PloS one
BACKGROUND: Loneliness is a distressing feeling that influences well-being. Immigrants' experience of acculturation to a new dominant culture places them at risk for maladaptive behaviors and daily rhythms leading to loneliness. Identifying daily-liv...

Key personality and training factors influencing athletes' mental health - based on machine learning.

PloS one
Athletes face a higher risk of mental health disorders compared to the general population, and prior theoretical and empirical work suggests that personality traits and training-related factors may play important roles in shaping athletes' mental hea...

Surface proteome of plasma extracellular vesicles differentiates between SARS-CoV-2 and influenza infection.

Virulence
Small extracellular vesicles (sEVs) play a role in the pathophysiology of viral respiratory infections and may be suitable biomarkers for COVID-19 and Influenza infections, or targets for treatment. We investigated differences in the surface proteome...