AI Article Synopsis
- - The study aimed to assess how well a group of ten otorhinolaryngologists agreed on prophylactic treatments for vestibular migraine (VM) and whether an assisted algorithm could help improve their decision-making process.
- - Initial agreement among the otolaryngologists was rated as "fair" (Fleiss' κ = .302), but after using the algorithm as an additional evaluator, the agreement improved significantly (Fleiss' κ = .711).
- - The algorithm's suggested treatments aligned closely with the otolaryngologists' choices, leading to enhanced consensus and indicating its potential utility in guiding treatment decisions.
Article Abstract
Background And Objective: Vestibular migraine (VM) is a cause of episodic vestibular syndrome. There are many drugs available for its prophylaxis and currently the choice is mainly made according to the patient's comorbidities. The aim of this article was to measure the agreement of a group of otorhinolaryngologists in the choice of a prophylactic treatment and to evaluate the role of an assisted algorithm in the choice of this prophylaxis.
Material And Method: The medical records of 10 patients with VM were offered to 10 otolaryngologists who were asked to select for each patient the drug they considered most appropriate among five possible options. The Fleiss' κ index was calculated among the 10 otolaryngologists alone, recalculating it including the algorithm as the eleventh evaluator, and Cohen's κ index was calculated between each otolaryngologist and the answers of the algorithm. The otolaryngologists were offered the option to change their responses after knowing the responses of the algorithm and then both indexes were calculated again.
Results: The Fleiss' κ index was .302. This index was raised to .343 after introducing the algorithm as an evaluator. After offering the responses proposed by the algorithm, Cohen's κ was improved in 9 of the 10 evaluators, and Fleiss' κ rose to .711.
Conclusions: The agreement between otorhinolaryngologists in choosing prophylaxis for MV can be defined as "fair". The responses of the algorithm for the choice of prophylaxis were close to the average opinion of the otolaryngologists, raising the agreement between them to "substantial".
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.otorri.2019.04.002 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Analyzing Secondary Cancer Risk: A Machine Learning Approach.
Asian Pac J Cancer Prev
January 2025
Department of Physics, Faculty of Sciences, Arak University, Arak, Iran.
Objective: Addressing the rising cancer rates through timely diagnosis and treatment is crucial. Additionally, cancer survivors need to understand the potential risk of developing secondary cancer (SC), which can be influenced by several factors including treatment modalities, lifestyle choices, and habits such as smoking and alcohol consumption. This study aims to establish a novel relationship using linear regression models between dose and the risk of SC, comparing different prediction methods for lung, colon, and breast cancer.
View Article and Find Full Text PDFThe Comparison of Cost-Effectiveness Between Magnetic Resonance Spectroscopy and Provocative Discography in the Identification of Chronic Low Back Pain Surgery Candidates.
Clinicoecon Outcomes Res
January 2025
Department of Orthopaedic Surgery, UC San Francisco, San Francisco, CA, 94143-0728, USA.
Background/context: Chronic low back pain (CLBP) is a significant US healthcare burden with millions of lumbar spine procedures annually. Diagnostic tests are essential to guide treatment but provocative discography (PD), the most common diagnostic procedure, is without robust evidence of its value. A non-invasive alternative using Magnetic Resonance Spectroscopy (MRS) offers a potential solution.
View Article and Find Full Text PDFCytoNorm 2.0: A flexible normalization framework for cytometry data without requiring dedicated controls.
Cytometry A
January 2025
Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium.
Cytometry is a single cell, high-dimensional, high-throughput technique that is being applied across a range of disciplines. However, many elements alongside the data acquisition process might give rise to technical variation in the dataset, called batch effects. CytoNorm is a normalization algorithm for batch effect removal in cytometry data that was originally published in 2020 and has been applied on a variety of datasets since then.
View Article and Find Full Text PDFFast optimization of the emission reduction pathways of major air pollutants in China: From the perspective of different decision preferences.
Environ Int
January 2025
Institute of Atmospheric Environment, Chinese Academy of Environmental Planning, Beijing 100012, China; Center of Synergistic Control for Reducing Pollution and Carbon Emissions, Chinese Academy of Environmental Planning, Beijing 100012, China. Electronic address:
To address the concern of optimization problem of China's PM control and the limitation of computational efficiencies for traditional air quality models, we developed an integrated analysis framework to efficiently establish the identification and cost-benefit assessment of PM control pathways in China by constructing a rapid PM exposure response method based on the high-order decoupled direct method (HDDM) and coupling the sequential least square algorithm (SLSQP) and health impact assessment model. Six emission reduction scenarios with varying decision preferences were analyzed. Our study provides a methodological approach for the rapid optimization of emission pathways of major air pollutants in China with flexible options in terms of objectives and constraints, fully considering the diverse differences in environmental, health, and economic impacts among different pollution sources simultaneously.
View Article and Find Full Text PDFA Comprehensive Analysis of a Social Intelligence Dataset and Response Tendencies Between Large Language Models (LLMs) and Humans.
Sensors (Basel)
January 2025
Department of Electronics and Electrical Engineering, Faculty of Science and Technology, Keio University, 3-14-1, Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan.
In recent years, advancements in the interaction and collaboration between humans and have garnered significant attention. Social intelligence plays a crucial role in facilitating natural interactions and seamless communication between humans and Artificial Intelligence (AI). To assess AI's ability to understand human interactions and the components necessary for such comprehension, datasets like Social-IQ have been developed.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!