AIMC Topic: Humans

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Explainable artificial intelligence model to predict acute critical illness from electronic health records.

Nature communications
Acute critical illness is often preceded by deterioration of routinely measured clinical parameters, e.g., blood pressure and heart rate. Early clinical prediction is typically based on manually calculated screening metrics that simply weigh these pa...

Prediction of the development of acute kidney injury following cardiac surgery by machine learning.

Critical care (London, England)
BACKGROUND: Cardiac surgery-associated acute kidney injury (CSA-AKI) is a major complication that results in increased morbidity and mortality after cardiac surgery. Most established prediction models are limited to the analysis of nonlinear relation...

Derivation of Breathing Metrics From a Photoplethysmogram at Rest: Machine Learning Methodology.

JMIR mHealth and uHealth
BACKGROUND: There has been a recent increased interest in monitoring health using wearable sensor technologies; however, few have focused on breathing. The ability to monitor breathing metrics may have indications both for general health as well as r...

Asthma Exacerbation Prediction and Risk Factor Analysis Based on a Time-Sensitive, Attentive Neural Network: Retrospective Cohort Study.

Journal of medical Internet research
BACKGROUND: Asthma exacerbation is an acute or subacute episode of progressive worsening of asthma symptoms and can have a significant impact on patients' quality of life. However, efficient methods that can help identify personalized risk factors an...

Precision Digital Oncology: Emerging Role of Radiomics-based Biomarkers and Artificial Intelligence for Advanced Imaging and Characterization of Brain Tumors.

Radiology. Imaging cancer
Advances in computerized image analysis and the use of artificial intelligence-based approaches for image-based analysis and construction of prediction algorithms represent a new era for noninvasive biomarker discovery. In recent literature, it has b...

Deep learning for cerebral angiography segmentation from non-contrast computed tomography.

PloS one
Cerebral computed tomography angiography is a widely available imaging technique that helps in the diagnosis of vascular pathologies. Contrast administration is needed to accurately assess the arteries. On non-contrast computed tomography, arteries a...

Machine learning approach to predict postoperative opioid requirements in ambulatory surgery patients.

PloS one
Opioids play a critical role in acute postoperative pain management. Our objective was to develop machine learning models to predict postoperative opioid requirements in patients undergoing ambulatory surgery. To develop the models, we used a periope...

MRI-guided lumbar spinal injections with body-mounted robotic system: cadaver studies.

Minimally invasive therapy & allied technologies : MITAT : official journal of the Society for Minimally Invasive Therapy
INTRODUCTION: This paper reports the system integration and cadaveric assessment of a body-mounted robotic system for MRI-guided lumbar spine injections. The system is developed to enable MR-guided interventions in closed bore magnet and avoid proble...

Automated Assessment of COVID-19 Reporting and Data System and Chest CT Severity Scores in Patients Suspected of Having COVID-19 Using Artificial Intelligence.

Radiology
Background The coronavirus disease 2019 (COVID-19) pandemic has spread across the globe with alarming speed, morbidity, and mortality. Immediate triage of patients with chest infections suspected to be caused by COVID-19 using chest CT may be of assi...

Self-initiations in young children with autism during Pivotal Response Treatment with and without robot assistance.

Autism : the international journal of research and practice
The initiation of social interaction is often defined as a core deficit of autism spectrum disorder. Optimizing these self-initiations is therefore a key component of Pivotal Response Treatment, an established intervention for children with autism sp...