Biomedical data-disadvantage is a health risk factor for the vast majority of the world’s population.
AI greatly empowers precision medicine, but in the meantime, opens up a major pathway for this risk factor to assert its effects.
AI-powered precision medicine is set to be less precise for the data-disadvantaged populations, which will produce new health disparities.
The new health disparities can impact any disease where data inequality exists, their negative impacts would be broad.
Transfer learning can reduce the negative impacts of data inequality, thereby mitigates the health disparities arising from data inequality.