AI, Other Technologies May Help Narrow Gender Disparities in Melanoma

Technology like artificial intelligence (AI) may help address gender disparities in melanoma, but a new report also suggests that lasting improvement will require a mix of innovative technologies and clearly targeted policy initiatives. Those conclusions were drawn in a review published last month in Dermatological Reviews.¹

Newer technology may play an important role in aiding early skin cancer diagnosis, new research suggests. | Image credit: InsideCreativeHouse - stock.adobe.com

Corresponding author Abdulqadir J. Nashwan, MSc, of Qatar University, and colleagues, wanted to better understand the biological, behavioral, and environmental factors underlying consistent findings that men with melanoma are statistically more likely to be diagnosed at a later stage, have more aggressive tumors, and die from the disease, compared to women.

Nashwan and colleagues noted that a wide range of factors have been identified as potential contributors to the gender disparities. For instance, men are more likely to have melanomas on their scalp and back, both places that can be difficult for patients to notice. Melanomas diagnosed in men are also more likely to have tissue invasion and rapid growth, they added. Yet, the investigators said that even after adjusting for body site and tumor thickness, women still have a significantly lower risk of death than men.²

“Researchers attribute these differences to factors such as estrogen receptor expression, immune responses, vitamin D metabolism, and the ability to neutralize oxidative stress, although further investigation is needed to fully understand the underlying mechanisms,” Nashwan and colleagues wrote.

Behavioral factors also appear to play a role in the disparity, the authors said. A 2021 survey of 705 men found only 17.1% reported wearing sunscreen on a daily basis, and 28.3% said they use it “infrequently.”³ Part of the reason, the survey found, is that men associated tanned skin with attractiveness and health. Men also tend to have higher sun exposure than women, Nashwan and colleagues wrote, due in part to occupational exposure to sun.

The investigators said newer technology may play an important role in aiding early diagnosis. One such tool is AI. AI models can analyze high-resolution dermoscopic and clinical images to classify lesions “with remarkable sensitivity and specificity,” Nashwan and colleagues wrote. The development of so-called “explainable AI,” or XAI, can also improve patient care by providing more clarity about why and how AI models draw their conclusions.

Yet, the authors noted that AI’s efficacy is largely based on the quality of the data sets used to train models, and many large data sets under-represent minority groups. Some sets also have significant gender imbalances, which could limit their ability to spot gender-specific melanoma patterns, they explained. A number of efforts are underway to try and mitigate these drawbacks.

“One successful approach integrates ‘super-prompts’ or region-specific demographic prompts into generative AI models to produce images reflecting the real-world distribution of skin tones,” they wrote.⁴ They said tools like bias-aware algorithms and repeated bias audits can also help mitigate these problems.

In addition to diagnosing melanoma, the authors noted AI can also be useful in supporting clinical decision-making.

“AI algorithms analyze complex patient data, including clinical history, molecular biomarkers, and genetic profiles, to predict treatment responses and recommend tailored therapeutic strategies,” they noted.

Aside from AI, though, Nashwan and colleagues said other innovations like liquid biopsies and the use of blood biomarkers can be leveraged to improve early diagnosis rates and real-time disease monitoring. They noted that liquid biopsies may also help offset disparities based on skin color, since they do not rely on visual assessment.

The investigators said policymakers can also help lessen disparities, through programs such as gender-specific and racially inclusive screening programs and public awareness campaigns about the risk of melanoma.

Ultimately, they said, solving the problem of melanoma gender disparities will require more than a single approach or technological advance.

“A gender-sensitive, AI-driven approach to precision medicine, complemented by comprehensive policy changes, can ultimately improve detection, treatment, and survival rates for all melanoma patients, especially high-risk male and minority groups,” they concluded.

References

1. Kakish DR, Alsamhori JF, Qaqish LN, et al. Gender disparities in melanoma: advances in diagnosis, treatment, and the role of artificial intelligence. Dermatol Rev. 2025;6(1):e70022. doi:10.1002/der2.70022.
2. Morgese F, Sampaolesi C, Torniai M, et al. Gender Differences and Outcomes in Melanoma Patients. Oncol Ther. 2020;8(1):103-114. doi:10.1007/s40487-020-00109-1
3. Adams GJ, Goldstein EK, Goldstein BG, Jarman KL, Goldstein AO. Attitudes and Behaviors That Impact Skin Cancer Risk among Men. Int J Environ Res Public Health. 2021;18(19):9989. doi:10.3390/ijerph18199989
4. O'Malley A, Veenhuizen M, Ahmed A. Ensuring Appropriate Representation in Artificial Intelligence-Generated Medical Imagery: Protocol for a Methodological Approach to Address Skin Tone Bias. JMIR AI. 2024;3:e58275. Published 2024 Nov 27. doi:10.2196/58275