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Oral Health Misinformation on Youtube - A Content Analysis.
J Pharm Bioallied Sci
December 2024
Department of Public Health Dentistry, CRRI, Sathyabama Dental College and Hospital, Chennai, Tamil Nadu, India.
Introduction: With the rise of social media and widespread smartphone use, information is now readily accessible worldwide. However, the credibility of this information often remains unchecked. Few studies have evaluated oral health content on online platforms.
View Article and Find Full Text PDFMisleading metrics in classification tasks: a closer look at negative predictive value in the context of post-ERCP pancreatitis prediction.
Gastrointest Endosc
March 2025
Gastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Quality and reliability evaluation of YouTube® exercises content for temporomandibular disorders.
BMC Oral Health
February 2025
Department of Physiotherapy and Rehabilitation, Faculty of Health Sciences, Tokat Gaziosmanpaşa University, Tokat, 60250, Turkey.
Objectives: YouTube is a popular source for health-related content, including exercises for temporomandibular disorders (TMD). This study aimed to evaluate the content and quality of YouTube videos on TMD exercises.
Methods: A systematic search on YouTube using keywords related to TMD exercises and rehabilitation identified relevant videos.
Assessing Algorithm Fairness Requires Adjustment for Risk Distribution Differences: Re-Considering the Equal Opportunity Criterion.
medRxiv
February 2025
Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, USA.
The proliferation of algorithm-assisted decision making has prompted calls for careful assessment of algorithm fairness. One popular fairness metric, equal opportunity, demands parity in true positive rates (TPRs) across different population subgroups. However, we highlight a critical but overlooked weakness in this measure: at a given decision threshold, TPRs vary when the underlying risk distribution varies across subgroups, even if the model equally captures the underlying risks.
View Article and Find Full Text PDFBedside implications of the use of surrogate endpoints in solid and haematological cancers: implications for our reliance on PFS, DFS, ORR, MRD and more.
BMJ Oncol
October 2024
Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, USA.
Clinical endpoints, such as overall survival, directly measure relevant outcomes. Surrogate endpoints, in contrast, are intermediate, stand-in measures of various tumour-related metrics and include tumour growth, tumour shrinkage, blood results, etc. Surrogates may be a time point measurement, that is, tumour shrinkage at some point (eg, response rate) or biomarker-assessed disease status, measured at given time points (eg, circulating tumour DNA, ctDNA).
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