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20212026
most citedDisparities in Dermatology AI: Assessments Using Diverse Clinical Images

511 citations · 1k across the 4 of their papers we have counts for

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5 papers

cs.AI2026

Correlation Is Not Enough: Embedding Human Metadata for Individual Causal Discovery

Suraj Biswas, Saurabh Gupta, Pritam Mukherjee

Ask a pretrained biomedical language model whether "cortisol 28 ug/dL" and "stock-market volatility" are related, and it returns a cosine similarity of 0.83 on a scale where 1.0 me…

cs.AI2026

You Are in Control of Your State: Why Human Outcomes Are Controllable Through Causal State Intervention

Suraj Biswas, Saurav Gupta, Pritam Mukherjee

A central puzzle for the behavioural sciences and for human-facing artificial intelligence is the persistence of within-person variability. The same individual, presented with the…

cs.CL2023

Utilizing Longitudinal Chest X-Rays and Reports to Pre-Fill Radiology Reports

Qingqing Zhu, Tejas Sudharshan Mathai, Pritam Mukherjee +3

Despite the reduction in turn-around times in radiology reports with the use of speech recognition software, persistent communication errors can significantly impact the interpreta…

eess.IV2022★ 494 cited

Disparities in Dermatology AI Performance on a Diverse, Curated Clinical Image Set

Roxana Daneshjou, Kailas Vodrahalli, Roberto A Novoa +16

Access to dermatological care is a major issue, with an estimated 3 billion people lacking access to care globally. Artificial intelligence (AI) may aid in triaging skin diseases.…

eess.IV2021★ 511 cited

Disparities in Dermatology AI: Assessments Using Diverse Clinical Images

Roxana Daneshjou, Kailas Vodrahalli, Weixin Liang +14

More than 3 billion people lack access to care for skin disease. AI diagnostic tools may aid in early skin cancer detection; however most models have not been assessed on images of…