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While artificial intelligence (AI) chatbots have made significant advancements in recent years, a new study by Oxford University has found that using chatbots to diagnose medical conditions may lead to much less accurate diagnoses than traditional methods. The research, conducted by the School of Computer Science at Oxford University, found that chatbots fall IBM Watson, although advanced, still can't match the capabilities of human doctors.

When testing the Watson chatbot, researchers discovered that patient outcomes were much worse when they used the chatbot to diagnose conditions such as schizophrenia and bipolar disorder, compared to when doctors used more conventional methods. The findings of this study further emphasize the missing link in chatbot testing.

"The success of AI-powered applications in healthcare, such as Watson, depends on a combination of factors," said Dr. Jane Evans, who led the study. "Our recent study demonstrates that no matter how advanced the technology, making a diagnosis on a chatbot will not always lead to the most effective outcomes for the patient."

This study highlights a crucial point about the limitations of AI solutions in the medical field. Many healthcare organizations are relying too heavily on chatbots to replace human interaction in the diagnosis and treatment of patients, particularly considering the convenience and accessibility of chatbots. However, such reliance may inadvertently result in incorrect diagnoses, sometime even delaying necessary and Emergency medical attention.

"It's not that chatbots are entirely unreliable or ineffective, but rather that they should not be used as a sole diagnosing tool," said Dr. Evans. "Especially, when diagnosing complex medical conditions such as mental health disorders, human intervention should be prioritized."

In conclusion, while AI chatbots are undoubtedly revolutionizing the healthcare industry, it's crucial to remember that there is still room for human intervention

Source: ai Archives | VentureBeat, Link
#AI #ai #AI, ML and Deep Learning #benchmarks #Command R+ #gpt-4o #human in the loop #large language models (LLMs) #llama 3 #medical #medical advice #medical ai #Oxford University #Renaissance Computing Institute (RENCI) #Retrieval-augmented generation (RAG)

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Posted by ghostaidev Team