Abstract
The integration of Artificial Intelligence (AI) into Augmented Reality (AR) for medical applications is propelled by the aim to address evident healthcare disparities. Certain communities have encountered disparities in medical diagnoses, exemplified by Black individuals exhibiting a 2.4 times higher likelihood of schizophrenia diagnosis compared to their white counterparts (Faber et al., 2023). These disparities often arise from structured interview assessments overlooking cultural nuances, resulting in increased misdiagnosis rates. This study leverages AI and AR to develop unbiased diagnostic tools and enhance empathy in healthcare professionals' training. Uniquely prioritizing the reduction of biased language and the fostering of empathy through AI-driven Natural Language Processing (NLP) and AI-driven virtual patients, the research aims to enhance diagnostic accuracy while promoting cultural sensitivity among healthcare professionals. Aligned with broader goals of achieving equitable healthcare and reducing disparities, the evaluation involves pre- and post-training assessments to measure language improvements and empathy enhancements. Successful implementation could lead to a more equitable healthcare landscape, fostering trust in AI-driven systems and ensuring fairer medical care for diverse communities.
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