While Artificial Intelligence (AI) revolutionizes medical diagnostics by analyzing vast amounts of patient data, predicting outcomes, and suggesting treatment plans, it faces several hurdles. Its accuracy is tied to the quality of the training data, which can be flawed leading to risky predictions in a medical context. Other contentious factors include patient privacy and accountability, requiring strict legal and ethical frameworks. AI also struggles with unexpected data anomalies and lacks human intelligence’s comprehension of context, reasoning, and judgment. Therefore, AI should assist, not substitute, human intelligence in healthcare. Despite AI’s remarkable potential, its limitations and challenges must remain in focus to ensure patient safety and care.
Full article here: https://medium.com/@lawsuithelpdesk/unraveling-the-intricacies-why-artificial-intelligence-sometimes-fails-us-in-medical-diagnoses-37f1bab62a11