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A Deep Learning–Based Rotten Food Recognition App for Older Adults: Development and Usability Study

A Deep Learning–Based Rotten Food Recognition App for Older Adults: Development and Usability Study

Popup that asks the user whether to use a photo. (C) Interface for displaying the results of classifying the freshness of the fruit: (C)-1. Text that indicates the type and freshness of the photographed fruit. (C)-2. Button to return to the home screen of the app so that the user can take a picture of another fruit. Questions to answer the research questions (1 for strongly disagree to 5 for strongly agree): I think it was easy to touch the app icon and review the first screen of the app.

Minki Chun, Ha-Jin Yu, Hyunggu Jung

JMIR Form Res 2024;8:e55342

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Photos Shared on Facebook in the Context of Safe Sleep Recommendations: Content Analysis of Images

Photos Shared on Facebook in the Context of Safe Sleep Recommendations: Content Analysis of Images

In posting her question, she shared a photo of her infant in the crib, in which there were multiple foreign objects present and the infant was sleeping prone. This resulted in other shared photos among the mothers. For instance, a mother commented, “This is how my son sleeps! We have used crib bumpers with all 3 of my kids” and included a photo of her infant sleeping prone in the crib with crib bumpers present. She also added there were “cute” crib bumpers available via Amazon.

Kelly Pretorius, Sookja Kang, Eunju Choi

JMIR Pediatr Parent 2024;7:e54610

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Article has an altmetric score of 14

Tailored Prompting to Improve Adherence to Image-Based Dietary Assessment: Mixed Methods Study

Tailored Prompting to Improve Adherence to Image-Based Dietary Assessment: Mixed Methods Study

Both standard and tailored text prompts read, “This is a reminder to record your photo food diary using the Easy Diet Diary app.” The number of images per participant per day was counted across the predefined recording dates. Images generated by the user were automatically uploaded to Easy Diet Diary Connect (Xyris Software) for image rate analysis at the end of each image-based dietary recording period. No analysis or interpretation of nutritional content in the image was performed.

Lachlan Lee, Rosemary Hall, James Stanley, Jeremy Krebs

JMIR Mhealth Uhealth 2024;12:e52074

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Article has an altmetric score of 7

Using AI Text-to-Image Generation to Create Novel Illustrations for Medical Education: Current Limitations as Illustrated by Hypothyroidism and Horner Syndrome

Using AI Text-to-Image Generation to Create Novel Illustrations for Medical Education: Current Limitations as Illustrated by Hypothyroidism and Horner Syndrome

Confidentiality concerns can limit traditional patient photo use, especially when facial features are essential [4]. Using widely available AI text-to-image tools, we aimed to create images portraying distinct facial signs important for medical trainees—hypothyroidism (myxedema) and Horner syndrome [5,6]. These tools generate unique, high-quality images based on text prompts, utilizing learned probability distributions rather than pre-existing images [7].

Ajay Kumar, Pierce Burr, Tim Michael Young

JMIR Med Educ 2024;10:e52155

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Article has an altmetric score of 4

Agreement Between Self-reports and Photos to Assess e-Cigarette Device and Liquid Characteristics in Wave 1 of the Vaping and Patterns of e-Cigarette Use Research Study: Web-Based Longitudinal Cohort Study

Agreement Between Self-reports and Photos to Assess e-Cigarette Device and Liquid Characteristics in Wave 1 of the Vaping and Patterns of e-Cigarette Use Research Study: Web-Based Longitudinal Cohort Study

Researchers (EC and JH) used the Google search engine to search text and markings in submitted photos of devices and liquids to identify the device brand and model and liquid brand and flavor by visually matching the submitted photo with Google search results.

Elizabeth Crespi, Jeffrey J Hardesty, Qinghua Nian, Joshua Sinamo, Kevin Welding, Ryan David Kennedy, Joanna E Cohen

J Med Internet Res 2022;24(4):e33656

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Article has an altmetric score of 1

Remote Rating of Atopic Dermatitis Severity Using Photo-Based Assessments: Proof-of-Concept and Reliability Evaluation

Remote Rating of Atopic Dermatitis Severity Using Photo-Based Assessments: Proof-of-Concept and Reliability Evaluation

In cases when one item could not be rated from the photograph, the dermatologist would choose “not applicable” for that specific item and the entire photo was consequently discarded. To calculate one single i SCORAD per patient, the mean of all available photographs for a patient was calculated. This i SCORAD was compared with the clinical assessment performed in person.

Zarqa Ali, Kristina Melbardis Joergensen, Anders Daniel Andersen, Andrei Chiriac, Theis Bjerre-Christensen, Ionela Manole, Ana-Maria Dutei, Irina Deaconescu, Alina Suru, Adina Serban, Ari Pall Isberg, Priyanka Dahiya, Simon Francis Thomsen, John Robert Zibert

JMIR Form Res 2021;5(5):e24766

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Article has an altmetric score of 2