AI Medical Compendium Topic:
Adult

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Evaluation of correctness and reliability of GPT, Bard, and Bing chatbots' responses in basic life support scenarios.

Scientific reports
Timely recognition and initiation of basic life support (BLS) before emergency medical services arrive significantly improve survival rates and neurological outcomes. In an era where health information-seeking behaviors have shifted toward online sou...

Communication challenges and experiences between parents and providers in South Korean paediatric emergency departments: a qualitative study to define AI-assisted communication agents.

BMJ open
OBJECTIVES: This study aimed to explore communication challenges between parents and healthcare providers in paediatric emergency departments (EDs) and to define the roles and functions of an artificial intelligence (AI)-assisted communication agent ...

Can artificial ıntelligence detect the anti-aging effect of rhinoplasty?

Journal of plastic surgery and hand surgery
BACKGROUND: The quest for eternal youth has been a common theme in many cultures for centuries. While we have yet to discover a way to preserve youth eternally, we have made significant progress in understanding the aging process and in developing ph...

Machine learning-based non-invasive continuous dynamic monitoring of human core temperature with wearable dual temperature sensors.

Physiological measurement
Due to the growing demand for personal health monitoring in extreme environments, continuous monitoring of core temperature has become increasingly important. Traditional monitoring methods, such as mercury thermometers and infrared thermometers, may...

Positive relationship between education level and risk perception and behavioral response: A machine learning approach.

PloS one
This paper aims to examine the influence mechanism of education level as a key situational factor in the relationship between risk perception and behavioral response, encompassing both behavioral intention and preparatory behavior. Utilizing non-para...

Personalized glucose forecasting for people with type 1 diabetes using large language models.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Type 1 Diabetes (T1D) is an autoimmune disease that requires exogenous insulin via Multiple Daily Injections (MDIs) or subcutaneous pumps to maintain targeted glucose levels. Despite the advances in Continuous Glucose Monito...

Neural networks can accurately identify individual runners from their foot kinematics, but fail to predict their running performance.

Journal of biomechanics
Athletes and coaches may seek to improve running performance through adjustments to running form. Running form refers to the biomechanical characteristics of a runner's movement, and can distinguish individual runners as well as groups of runners, su...

Automated segmentation of the dorsal root ganglia in MRI.

NeuroImage
The dorsal root ganglion (DRG) contains all primary sensory neurons, but its functional role in somatosensory and pain processing remains unclear. Recently, MR imaging techniques have been developed for objective in vivo observation of the DRG. In pa...

Electrocardiographic Discrimination of Long QT Syndrome Genotypes: A Comparative Analysis and Machine Learning Approach.

Sensors (Basel, Switzerland)
Long QT syndrome (LQTS) presents a group of inheritable channelopathies with prolonged ventricular repolarization, leading to syncope, ventricular tachycardia, and sudden death. Differentiating LQTS genotypes is crucial for targeted management and tr...

Artificial intelligence-based personalised rituximab treatment protocol in membranous nephropathy (iRITUX): protocol for a multicentre randomised control trial.

BMJ open
INTRODUCTION: Membranous nephropathy is an autoimmune kidney disease and the most common cause of nephrotic syndrome in non-diabetic Caucasian adults. Rituximab is now recommended as first-line therapy for membranous nephropathy. However, Kidney Dise...