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An AI deep learning algorithm for detecting pulmonary nodules on ultra-low-dose CT in an emergency setting: a reader study.

European radiology experimental
BACKGROUND: To retrospectively assess the added value of an artificial intelligence (AI) algorithm for detecting pulmonary nodules on ultra-low-dose computed tomography (ULDCT) performed at the emergency department (ED).

Explainable predictions of a machine learning model to forecast the postoperative length of stay for severe patients: machine learning model development and evaluation.

BMC medical informatics and decision making
BACKGROUND: Predicting the length of stay in advance will not only benefit the hospitals both clinically and financially but enable healthcare providers to better decision-making for improved quality of care. More importantly, understanding the lengt...

Tickling induces a unique type of spontaneous laughter.

Biology letters
Laughing is ubiquitous in human life, yet what causes it and how it sounds is highly variable. Considering this diversity, we sought to test whether there are fundamentally different kinds of laughter. Here, we sampled spontaneous laughs ( = 887) fro...

I-SIRch: AI-powered concept annotation tool for equitable extraction and analysis of safety insights from maternity investigations.

International journal of population data science
BACKGROUND: Maternity care is a complex system involving treatments and interactions between patients, healthcare providers, and the care environment. To enhance patient safety and outcomes, it is crucial to understand the human factors (e.g. individ...

The help-seeking process and predictors of mental health care use among individuals with depressive symptoms: a machine learning approach.

Frontiers in public health
PURPOSE: The goal of the study was to identify the most important influences on professional healthcare use of people with depressive symptoms. We incorporated findings from research areas of health behaviors, stigma, and motivation to predict the he...

An accurate prediction for respiratory diseases using deep learning on bronchoscopy diagnosis images.

Journal of advanced research
INTRODUCTION: Bronchoscopy is of great significance in diagnosing and treating respiratory illness. Using deep learning, a diagnostic system for bronchoscopy images can improve the accuracy of tracheal, bronchial, and pulmonary disease diagnoses for ...

Machine Learning Algorithms Exceed Comorbidity Indices in Prediction of Short-Term Complications After Hip Fracture Surgery.

The Journal of the American Academy of Orthopaedic Surgeons
BACKGROUND: Hip fractures are among the most morbid acute orthopaedic injuries often due to accompanying patient frailty. The purpose of this study was to determine the reliability of assessing surgical risk after hip fracture through machine learnin...

Impact of Deep Learning-Based Computer-Aided Detection and Electronic Notification System for Pneumothorax on Time to Treatment: Clinical Implementation.

Journal of the American College of Radiology : JACR
OBJECTIVE: To assess whether the implementation of deep learning (DL) computer-aided detection (CAD) that screens for suspected pneumothorax (PTX) on chest radiography (CXR) combined with an electronic notification system (ENS) that simultaneously al...

Machine learning-based prediction of elevated N terminal pro brain natriuretic peptide among US general population.

ESC heart failure
AIMS: Natriuretic peptide-based pre-heart failure screening has been proposed in recent guidelines. However, an effective strategy to identify screening targets from the general population, more than half of which are at risk for heart failure or pre...