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Artificial Intelligence Portrayals in Orthopaedic Surgery: An Analysis of Gender and Racial Diversity Using Text-to-Image Generators.

The Journal of bone and joint surgery. American volume
BACKGROUND: The increasing accessibility of artificial intelligence (AI) text-to-image generators offers a novel avenue for exploring societal perceptions. The present study assessed AI-generated images to examine the representation of gender and rac...

Machine Learning for Movement Pattern Changes during Kinect-Based Mixed Reality Exercise Programs in Women with Possible Sarcopenia: Pilot Study.

Annals of geriatric medicine and research
BACKGROUND: Sarcopenia is a muscle-wasting condition that affects older individuals. It can lead to changes in movement patterns, which can increase the risk of falls and other injuries.

Development, validation, and usability evaluation of machine learning algorithms for predicting personalized red blood cell demand among thoracic surgery patients.

International journal of medical informatics
INTRODUCTION: Preparing appropriate red blood cells (RBCs) before surgery is crucial for improving both the efficacy of perioperative workflow and patient safety. In particular, thoracic surgery (TS) is a procedure that requires massive transfusion w...

Information extraction from medical case reports using OpenAI InstructGPT.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Researchers commonly use automated solutions such as Natural Language Processing (NLP) systems to extract clinical information from large volumes of unstructured data. However, clinical text's poor semantic structure and dom...

Machine/deep learning-assisted hemoglobin level prediction using palpebral conjunctival images.

British journal of haematology
Palpebral conjunctival hue alteration is used in non-invasive screening for anaemia, whereas it is a qualitative measure. This study constructed machine/deep learning models for predicting haemoglobin values using 150 palpebral conjunctival images ta...

Automatic detection of sleep apnea from a single-lead ECG signal based on spiking neural network model.

Computers in biology and medicine
BACKGROUND: Sleep apnea (SLA) is a commonly encountered sleep disorder characterized by repetitive cessation of respiration while sleeping. In the past few years, researchers have focused on developing less complex and more cost-effective diagnostic ...

A machine-learning approach for stress detection using wearable sensors in free-living environments.

Computers in biology and medicine
Stress is a psychological condition resulting from the body's response to challenging situations, which can negatively impact physical and mental health if experienced over prolonged periods. Early detection of stress is crucial to prevent chronic he...

Comparison of automated deep neural network against manual sleep stage scoring in clinical data.

Computers in biology and medicine
OBJECTIVE: To compare the accuracy and generalizability of an automated deep neural network and the Philip Sleepware G3™ Somnolyzer system (Somnolyzer) for sleep stage scoring using American Academy of Sleep Medicine (AASM) guidelines.

Prediction of prognosis in lung cancer using machine learning with inter-institutional generalizability: A multicenter cohort study (WJOG15121L: REAL-WIND).

Lung cancer (Amsterdam, Netherlands)
OBJECTIVES: Predicting the prognosis of lung cancer is crucial for providing optimal medical care. However, a method to accurately predict the overall prognosis in patients with stage IV lung cancer, even with the use of machine learning, has not bee...