AIMC Topic: Humans

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Deep-SAGA: a deep-learning-based system for automatic gaze annotation from eye-tracking data.

Behavior research methods
With continued advancements in portable eye-tracker technology liberating experimenters from the restraints of artificial laboratory designs, research can now collect gaze data from real-world, natural navigation. However, the field lacks a robust me...

Systematic review of artificial intelligence-based image diagnosis for inflammatory bowel disease.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
OBJECTIVES: Diagnosis of inflammatory bowel diseases (IBD) involves combining clinical, laboratory, endoscopic, histologic, and radiographic data. Artificial intelligence (AI) is rapidly being developed in various fields of medicine, including IBD. B...

CT-Derived Body Composition Assessment as a Prognostic Tool in Oncologic Patients: From Opportunistic Research to Artificial Intelligence-Based Clinical Implementation.

AJR. American journal of roentgenology
CT-based body composition measures are well established in research settings as prognostic markers in oncologic patients. Numerous retrospective studies have shown the role of objective measurements extracted from abdominal CT images of skeletal musc...

Prediction of preterm birth using artificial intelligence: a systematic review.

Journal of obstetrics and gynaecology : the journal of the Institute of Obstetrics and Gynaecology
Preterm birth is the leading cause of neonatal death. It is challenging to predict preterm birth. We elucidated the state of artificial intelligence research on the prediction of preterm birth, clarifying the predictive values and accuracy. We perfor...

Novel Pediatric Height Outlier Detection Methodology for Electronic Health Records via Machine Learning With Monotonic Bayesian Additive Regression Trees.

Journal of pediatric gastroenterology and nutrition
OBJECTIVE: To create a new methodology that has a single simple rule to identify height outliers in the electronic health records (EHR) of children.

Harmonization of Physiological Data in Neurocritical Care: Challenges and a Path Forward.

Neurocritical care
Continuous multimodal monitoring in neurocritical care provides valuable insights into the dynamics of the injured brain. Unfortunately, the "readiness" of this data for robust artificial intelligence (AI) and machine learning (ML) applications is lo...

Development and Validation of a Deep Learning Model to Predict the Occurrence and Severity of Retinopathy of Prematurity.

JAMA network open
IMPORTANCE: Retinopathy of prematurity (ROP) is the leading cause of childhood blindness worldwide. Prediction of ROP before onset holds great promise for reducing the risk of blindness.