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Use of Large Language Models to Classify Epidemiological Characteristics in Synthetic and Real-World Social Media Posts About Conjunctivitis Outbreaks: Infodemiology Study

Use of Large Language Models to Classify Epidemiological Characteristics in Synthetic and Real-World Social Media Posts About Conjunctivitis Outbreaks: Infodemiology Study

If there is content about drugs or drug usage (i.e. smoking weed, pot, marijuana, a joint, a bowl, a bong), getting high, sparking up, other slang terms like \“Mary Jane\”, \“bud\”, \“ganga\”, \“reefer\”, \“chronic\”, \“herb\”, \“spliff\”, \“roach\”, \“a j\”) then consider the type of outbreak as \“environmental - drugs\”. If you determine that the cause is infectious, please also tell us whether it is viral or bacterial.

Michael S Deiner, Russell Y Deiner, Cherie Fathy, Natalie A Deiner, Vagelis Hristidis, Stephen D McLeod, Thomas J Bukowski, Thuy Doan, Gerami D Seitzman, Thomas M Lietman, Travis C Porco

J Med Internet Res 2025;27:e65226

Influence of Virtual Reality Illusions on Balance Performance and Immersive User Experience in Young Adults: A Within-Subject Experimental Study

Influence of Virtual Reality Illusions on Balance Performance and Immersive User Experience in Young Adults: A Within-Subject Experimental Study

They kept their feet shoulder-width apart (approximately 40 cm), centered on the cross mark, and wore the HMD while staring straight ahead to align with the table in the game. Then, they were instructed to return the ball according to the general table tennis rules and to play without moving the feet from their starting position. In addition, participants were instructed that they could stop playing the game if they felt any discomfort, such as dizziness or nausea.

R Achintha M Abayasiri, Antonio Padilha Lanari Bo, Taylor J M Dick, Nilufar Baghaei

JMIR Serious Games 2025;13:e70376

Public Perception of the Brain-Computer Interface Based on a Decade of Data on X: Mixed Methods Study

Public Perception of the Brain-Computer Interface Based on a Decade of Data on X: Mixed Methods Study

The data underwent preprocessing, which involved omitting any mentions, URLs, and hashtags, removing any line breaks, deleting any HTML characters, replacing them with their respective Unicode equivalent, eliminating any special characters or punctuation points except exclamation points (the only punctuation mark relevant for sentiment analysis), and excluding posts from users with fewer than 10 followers to minimize “bot” influence and duplicate entries.

Mohammed A Almanna, Lior M Elkaim, Mohammed A Alvi, Jordan J Levett, Ben Li, Muhammad Mamdani, Mohammed Al‑Omran, Naif M Alotaibi

JMIR Form Res 2025;9:e60859