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Random survival forest for predicting the combined effects of multiple physiological risk factors on all-cause mortality.

Scientific reports
Understanding the combined effects of risk factors on all-cause mortality is crucial for implementing effective risk stratification and designing targeted interventions, but such combined effects are understudied. We aim to use survival-tree based ma...

Positive public attitudes towards agricultural robots.

Scientific reports
Robot technologies could lead to radical changes in farming. But what does the public know and think about agricultural robots? Recent experience with other agricultural technologies-such as plant genetic engineering-shows that public perceptions can...

A privacy-preserving platform oriented medical healthcare and its application in identifying patients with candidemia.

Scientific reports
Federated learning (FL) has emerged as a significant method for developing machine learning models across multiple devices without centralized data collection. Candidemia, a critical but rare disease in ICUs, poses challenges in early detection and t...

Artificial intelligence detects awareness of functional relation with the environment in 3 month old babies.

Scientific reports
A recent experiment probed how purposeful action emerges in early life by manipulating infants' functional connection to an object in the environment (i.e., tethering an infant's foot to a colorful mobile). Vicon motion capture data from multiple inf...

Development and validation of machine learning models to predict MDRO colonization or infection on ICU admission by using electronic health record data.

Antimicrobial resistance and infection control
BACKGROUND: Multidrug-resistant organisms (MDRO) pose a significant threat to public health. Intensive Care Units (ICU), characterized by the extensive use of antimicrobial agents and a high prevalence of bacterial resistance, are hotspots for MDRO p...

Automatic soft-tissue analysis on orthodontic frontal and lateral facial photographs based on deep learning.

Orthodontics & craniofacial research
BACKGROUND: To establish the automatic soft-tissue analysis model based on deep learning that performs landmark detection and measurement calculations on orthodontic facial photographs to achieve a more comprehensive quantitative evaluation of soft t...

Validation of an Electronic Health Record-Based Machine Learning Model Compared With Clinical Risk Scores for Gastrointestinal Bleeding.

Gastroenterology
BACKGROUND & AIMS: Guidelines recommend use of risk stratification scores for patients presenting with gastrointestinal bleeding (GIB) to identify very-low-risk patients eligible for discharge from emergency departments. Machine learning models may o...