AIMC Topic: Prospective Studies
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Development and Validation of a Machine Learning Model for Detection and Classification of Vertigo.
The Laryngoscope
Dec 19, 2024
PURPOSE: This study aims to investigate whether artificial intelligence can improve the diagnostic accuracy of vertigo related diseases.
Evaluating LLM-based generative AI tools in emergency triage: A comparative study of ChatGPT Plus, Copilot Pro, and triage nurses.
The American journal of emergency medicine
Dec 19, 2024
BACKGROUND: The number of emergency department (ED) visits has been on steady increase globally. Artificial Intelligence (AI) technologies, including Large Language Model (LLMs)-based generative AI models, have shown promise in improving triage accur...
Predicting Early recurrence of atrial fibrilation post-catheter ablation using machine learning techniques.
BMC cardiovascular disorders
Dec 19, 2024
BACKGROUND: Catheter ablation is a common treatment for atrial fibrillation (AF), but recurrence rates remain variable. Predicting the success of catheter ablation is crucial for patient selection and management. This research seeks to create a machi...
Optimizing the management of immune-related adverse events and survival in patients with thoracic cancer receiving immunotherapy through artificial intelligence (electronic patient-reported outcomes): The IMPATHI study.
Bulletin du cancer
Dec 18, 2024
INTRODUCTION: The lung cancer continues to be the primary cause of cancer-related deaths, despite significant advancements in treatment through the introduction of immunological checkpoint inhibitors (ICI). These inhibitors, initially used as monothe...
Prediction of new-onset atrial fibrillation in patients with hypertrophic cardiomyopathy using machine learning.
European journal of heart failure
Dec 18, 2024
AIMS: Atrial fibrillation (AF) is the most common sustained arrhythmia among patients with hypertrophic cardiomyopathy (HCM), leading to increased symptom burden and risk of thromboembolism. The HCM-AF score was developed to predict new-onset AF in p...
Cost-effectiveness analysis of AI-based image quality control for perinatal ultrasound screening.
BMC medical education
Dec 18, 2024
PURPOSE: This study aimed to compare the cost-effectiveness of AI-based approaches with manual approaches in ultrasound image quality control (QC).
Accuracy of symptom checker for the diagnosis of sexually transmitted infections using machine learning and Bayesian network algorithms.
BMC infectious diseases
Dec 18, 2024
BACKGROUND: A significant proportion of individuals with symptoms of sexually transmitted infection (STI) delay or avoid seeking healthcare, and digital diagnostic tools may prompt them to seek healthcare earlier. Unfortunately, none of the currently...
Line-field confocal optical coherence tomography coupled with artificial intelligence algorithms as tool to investigate wound healing: A prospective, randomized, single-blinded pilot study.
Journal of the European Academy of Dermatology and Venereology : JEADV
Dec 17, 2024
BACKGROUND: Ablative fractional photothermolysis serves as an excellent in vivo model for studying wound healing. The advent of non-invasive imaging devices, such as line-field confocal optical coherence tomography (LC-OCT), enhances this model by en...
Use of Hearing Aids Embedded with Inertial Sensors and Artificial Intelligence to Identify Patients at Risk for Falling.
Otology & neurotology : official publication of the American Otological Society, American Neurotology Society [and] European Academy of Otology and Neurotology
Dec 17, 2024
OBJECTIVE: To compare fall risk scores of hearing aids embedded with inertial measurement units (IMU-HAs) and powered by artificial intelligence (AI) algorithms with scores by trained observers.
Predicting grip strength-related frailty in middle-aged and older Chinese adults using interpretable machine learning models: a prospective cohort study.
Frontiers in public health
Dec 17, 2024
INTRODUCTION: Frailty is an emerging global health burden, and there is no consensus on the precise prediction of frailty. We aimed to explore the association between grip strength and frailty and interpret the optimal machine learning (ML) model usi...
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