AI applications in healthcare, such as diagnostics and treatment optimization, bring significant benefits but also raise ethical concerns, such as data breaches, biased algorithms, transparency, and patient consent. To ensure patient trust and safety, solutions such as data encryption, diverse algorithm training, and ongoing monitoring are needed. A collaborative approach involving diverse perspectives and stakeholders, including ethicists, healthcare professionals, and patient advocacy groups, is key to developing ethical, user-centric AI systems.
The True Cost of Focusing on Cost Instead of Cost-Effectiveness
When payors consider only the cost of the medication and not the cost and risk to the patient, doctor, and healthcare system, the irony is
