AI Medical Compendium Topic:
Cross-Sectional Studies

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Prediction of physical violence in schizophrenia with machine learning algorithms.

Psychiatry research
Patients with schizophrenia have been shown to have an increased risk for physical violence. While certain features have been identified as risk factors, it has been difficult to integrate these variables to identify violent patients. The present stu...

Machine-Learning prediction of comorbid substance use disorders in ADHD youth using Swedish registry data.

Journal of child psychology and psychiatry, and allied disciplines
BACKGROUND: Children with attention-deficit/hyperactivity disorder (ADHD) have a high risk for substance use disorders (SUDs). Early identification of at-risk youth would help allocate scarce resources for prevention programs.

Creation and Testing of a Deep Learning Algorithm to Automatically Identify and Label Vessels, Nerves, Tendons, and Bones on Cross-sectional Point-of-Care Ultrasound Scans for Peripheral Intravenous Catheter Placement by Novices.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: We sought to create a deep learning (DL) algorithm to identify vessels, bones, nerves, and tendons on transverse upper extremity (UE) ultrasound (US) images to enable providers new to US-guided peripheral vascular access to identify anato...

Deep Learning for Automated Sorting of Retinal Photographs.

Ophthalmology. Retina
PURPOSE: Though the domain of big data and artificial intelligence in health care continues to evolve, there is a lack of systemic methods to improve data quality and streamline the preparation process. To address this, we aimed to develop an automat...

Attitudes of Patients and Their Relatives Toward Artificial Intelligence in Neurosurgery.

World neurosurgery
BACKGROUND: Artificial intelligence (AI) may favorably support surgeons but can result in concern among patients and their relatives. The aim of this study was to evaluate attitudes of patients and their relatives regarding use of AI in neurosurgery.

AppendiXNet: Deep Learning for Diagnosis of Appendicitis from A Small Dataset of CT Exams Using Video Pretraining.

Scientific reports
The development of deep learning algorithms for complex tasks in digital medicine has relied on the availability of large labeled training datasets, usually containing hundreds of thousands of examples. The purpose of this study was to develop a 3D d...

Using machine learning to classify suicide attempt history among youth in medical care settings.

Journal of affective disorders
BACKGROUND: The current study aimed to classify recent and lifetime suicide attempt history among youth presenting to medical settings using machine learning (ML) as applied to a behavioral health screen self-report survey.

Auto detecting deliveries in elite cricket fast bowlers using microsensors and machine learning.

Journal of sports sciences
Cricket fast bowlers are at a high risk of injury occurrence, which has previously been shown to be correlated to bowling workloads. This study aimed to develop and test an algorithm that can automatically, reliably and accurately detect bowling deli...

Using a machine learning approach to predict mortality in critically ill influenza patients: a cross-sectional retrospective multicentre study in Taiwan.

BMJ open
OBJECTIVES: Current mortality prediction models used in the intensive care unit (ICU) have a limited role for specific diseases such as influenza, and we aimed to establish an explainable machine learning (ML) model for predicting mortality in critic...