AIMC Topic:
Young Adult

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Prediction of intra-abdominal injury using natural language processing of electronic medical record data.

Surgery
BACKGROUND: This study aimed to use natural language processing to predict the presence of intra-abdominal injury using unstructured data from electronic medical records.

An artificial intelligence-driven support tool for prediction of urine culture test results.

Clinica chimica acta; international journal of clinical chemistry
BACKGROUND AND AIMS: We aimed to develop an easily deployable artificial intelligence (AI)-driven model for rapid prediction of urine culture test results.

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...

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...

An auto-segmented multi-time window dual-scale neural network for brain-computer interfaces based on event-related potentials.

Journal of neural engineering
Event-related potentials (ERPs) are cerebral responses to cognitive processes, also referred to as cognitive potentials. Accurately decoding ERPs can help to advance research on brain-computer interfaces (BCIs). The spatial pattern of ERP varies with...

Nursing workload: use of artificial intelligence to develop a classifier model.

Revista latino-americana de enfermagem
OBJECTIVE: to describe the development of a predictive nursing workload classifier model, using artificial intelligence.

DNN-BP: a novel framework for cuffless blood pressure measurement from optimal PPG features using deep learning model.

Medical & biological engineering & computing
Continuous blood pressure (BP) provides essential information for monitoring one's health condition. However, BP is currently monitored using uncomfortable cuff-based devices, which does not support continuous BP monitoring. This paper aims to introd...

Neuroimaging and natural language processing-based classification of suicidal thoughts in major depressive disorder.

Translational psychiatry
Suicide is a growing public health problem around the world. The most important risk factor for suicide is underlying psychiatric illness, especially depression. Detailed classification of suicide in patients with depression can greatly enhance perso...

Identifying Key Training Load and Intensity Indicators in Ice Hockey Using Unsupervised Machine Learning.

Research quarterly for exercise and sport
To identify key training load (TL) and intensity indicators in ice hockey, practice, and game data were collected using a wearable 200-Hz accelerometer and heart rate (HR) recording throughout a four-week (29 days) competitive period (23 practice ses...

Machine learning predicts peak oxygen uptake and peak power output for customizing cardiopulmonary exercise testing using non-exercise features.

European journal of applied physiology
PURPOSE: Cardiopulmonary exercise testing (CPET) is considered the gold standard for assessing cardiorespiratory fitness. To ensure consistent performance of each test, it is necessary to adapt the power increase of the test protocol to the physical ...