AIMC Topic: Adenoidectomy
Clear Filters Showing 1 to 5 of 5 articles
Navigating ChatGPT's alignment with expert consensus on pediatric OSA management.
International journal of pediatric otorhinolaryngology
Oct 15, 2024
OBJECTIVE: This study aimed to evaluate the potential integration of artificial intelligence (AI), specifically ChatGPT, into healthcare decision-making, focusing on its alignment with expert consensus statements regarding the management of persisten...
Artificial intelligence and ChatGPT: An otolaryngology patient's ally or foe?
American journal of otolaryngology
Jan 9, 2024
BACKGROUND: As artificial intelligence (AI) is integrating into the healthcare sphere, there is a need to evaluate its effectiveness in the various subspecialties of medicine, including otolaryngology. Our study intends to provide a cursory review of...
Predicting polysomnographic severity thresholds in children using machine learning.
Pediatric research
May 9, 2020
BACKGROUND: Approximately 500,000 children undergo tonsillectomy and adenoidectomy (T&A) annually for treatment of obstructive sleep disordered breathing (oSDB). Although polysomnography is beneficial for preoperative risk stratification in these chi...
Oximetry
Adenoidectomy
Decision Making
Female
Risk
Hypersensitivity
Tonsillectomy
Asthma
Actigraphy
Polysomnography
Child
Sleep Apnea, Obstructive
Signal Processing, Computer-Assisted
Machine Learning
Male
Humans
Monitoring, Physiologic
Surveys and Questionnaires
Sleep Apnea Syndromes
Algorithms
Anthropometry
Evaluating advanced AI reasoning models: ChatGPT-4.0 and DeepSeek-R1 diagnostic performance in otolaryngology: a comparative analysis.
American journal of otolaryngology
Jan 1, 2025
PURPOSE: This study aimed to evaluate the diagnostic accuracy, comprehensiveness, and clinical relevance of two advanced artificial intelligence (AI) models, OpenAI's ChatGPT-4.0 and DeepSeek-R1, in the field of otolaryngology.
Data-driven Machine Learning Models for Risk Stratification and Prediction of Emergence Delirium in Pediatric Patients Underwent Tonsillectomy/Adenotonsillectomy.
Annali italiani di chirurgia
Jan 1, 2024
AIM: In the pediatric surgical population, Emergence Delirium (ED) poses a significant challenge. This study aims to develop and validate machine learning (ML) models to identify key features associated with ED and predict its occurrence in children ...
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 30978
- Neural Networks, Computer 29696
- Algorithms 26813
- Deep Learning 26324
- Artificial Intelligence 24267
- Robotics 13307
- Image Processing, Computer-Assisted 9512
- Retrospective Studies 9097
- Magnetic Resonance Imaging 6173
- Reproducibility of Results 5589
- Tomography, X-Ray Computed 4765
- Support Vector Machine 4678
- Computational Biology 4229
- Brain 4045
- Computer Simulation 3877
Recent Journals
- Scientific reports 5865
- Sensors (Basel, Switzerland) 4794
- PloS one 4011
- Neural networks : the official journal of the International Neural Network Society 2928
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1129
- Journal of chemical information and modeling 994
- Nature communications 938
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 850
- IEEE transactions on neural networks and learning systems 823