Labeling medical test results as ‘normal’ or ‘abnormal’ helps clinicians make quick judgments when diagnosing patients. But this binary approach to interpreting tests can lead to fatal errors.
Articles on medical decision-making
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A Carnegie Mellon researcher explains the connection between our brains and AI chatbots – and what a new Pennsylvania lawsuit reveals about the dangers of AI.
Two studies in the field of perinatal care show how, in the areas of breastfeeding and obstetrics, science prioritizes risk and the baby at the expense of mothers’ well-being.
Future AI large language models like Google’s AMIE might prove to fill gaps in health-care delivery, however, they must be adopted with caution.
