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FRIDAY, March 22, 2024 (HealthDay News) -- Most patients report an increase in trust in the quality of their medical care if asked for permission to use their images for research or education, according to a research letter published online March 13 in JAMA Dermatology.Trina Salvador, from the Memorial Sloan Kettering Cancer Center in New York City, and colleagues conducted a survey study to elucidate perspectives on image use, consent, and identifiability to inform practices for protecting privacy. Overall, 1,316 English-speaking U.S. adults were recruited; respondents completed a 29-item cross-sectional survey.The researchers found that 64.1 percent of respondents reported no change in trust in the quality of their care if their images were used for research or education. If they were asked for permission to use their images, 56.3 and 40.5 percent reported an increase in trust and no change in trust, respectively. Comfort with use of their clinical images was reported for publication in a journal, training artificial intelligence models, presentation at an academic conference, and education of students and medical trainees (45.3, 54.6, 45.3, and 62.0 percent, respectively). Overall, 45.0 and 51.6 percent reported concern and little or no concern with identifiability, respectively. Most of the respondents (84.9 percent) were comfortable with use of nonidentifiable images, while only 21.1 percent were comfortable with use of identifiable images. The majority of respondents preferred to be asked before use of nonidentifiable and identifiable images (88.6 and 97.7 percent, respectively)."Findings of this study highlight the need for transparent and standardized consent and deidentification processes," the authors write.<a target="_blank" rel="noopener noreferrer" href="https://jamanetwork.com/journals/jamadermatology/article-abstract/2815805">Abstract/Full Text (subscription or payment may be required)</a>

Most patients report an increase in trust in quality of medical care if they were asked for consent to use medical image

Survey Assesses Perspectives on Patient Image Use in Dermatology

FRIDAY, Feb. 16, 2024 (HealthDay News) -- Deep learning-aided decision support improves diagnostic accuracy for skin disease, according to a study published online Feb. 5 in Nature Medicine.Matthew Groh, Ph.D., from the Northwestern University Kellogg School of Management in Evanston, Illinois, and colleagues presented results from a study involving 389 board-certified dermatologists and 459 primary care physicians, which assessed the accuracy of diagnoses submitted by physicians in a store-and-forward teledermatology simulation. Physicians were asked to submit up to four differential diagnoses for 364 images spanning 46 skin diseases.The researchers found that the diagnostic accuracies were 38 and 19 percent, respectively, for specialists and generalists. For diagnosis of images of dark versus light skin, both specialists and generalists were 4 percentage points less accurate. The diagnostic accuracy of both specialists and generalists was improved by more than 33 percent with fair deep learning system decision support; the gap in diagnostic accuracy of generalists was exacerbated across skin tones."This study allows us to see not only how artificial intelligence assistance influences, but how it influences across levels of expertise," Groh said in a statement. "What might be going on there is that the primary care physicians don't have as much experience, so they don't know if they should rule a disease out or not because they aren't as deep into the details of how different skin diseases might look on different shades of skin."One author disclosed ties to the biotechnology industry.<a target="_blank" rel="noopener noreferrer" href="https://www.nature.com/articles/s41591-023-02728-3">Abstract/Full Text</a>

Both specialists and generalists were 4 percentage points less accurate for diagnosis of images of dark versus light skin

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Survey Assesses Perspectives on Patient Image Use in Dermatology

Deep Learning Improves Diagnostic Accuracy for Skin Diseases