Doctor ChatGPT Will See you Now!
By TMCnet Staff
Recently, a new Artificial Intelligence (AI) model called ChatGPT has been gaining attention for its ability to perform a wide range of natural language tasks. Developed by OpenAI, ChatGPT is a Large Language Model (LLM) that is trained to predict the likelihood of a given sequence of words based on the context of the words that come before it. This means that if it is trained on large amounts of text data, it can generate novel sequences of words that represent plausible sequences based on human language.
LLMs like ChatGPT have the potential to revolutionize various industries, including healthcare. In a recent study, researchers evaluated the performance of ChatGPT on the United States Medical Licensing Exam (USMLE), which consists of three exams: Step 1, Step 2CK, and Step 3. The results showed that ChatGPT performed at or near the passing threshold for all three exams without any specialized training or reinforcement. Additionally, ChatGPT demonstrated a high level of concordance and insight in its explanations.
This study suggests that large language models like ChatGPT may have potential in assisting with medical education and possibly even clinical decision-making. However, the authors of the study also mention that the development of clinical AI models requires significant time, resources, and domain-specific training data, which is currently in short supply in the healthcare industry.
The healthcare industry has been slow to adopt AI compared to other industries. The proliferation of clinical free-text fields combined with a lack of general interoperability between health IT systems contribute to a paucity of structured, machine-readable data required for the development of deep learning algorithms. Even when algorithms applicable to clinical care are developed, their quality tends to be highly variable, with many failing to generalize across settings due to limited technical, statistical, and conceptual reproducibility. As a result, the overwhelming majority of successful healthcare applications currently support back-office functions ranging from payor operations, automated prior authorization processing, and management of supply chains and cybersecurity threats. With rare exceptions - even in medical imaging - there are relatively few applications of AI directly used in widespread clinical care today.
One of the key developments that enabled image-based AI in clinical imaging has been the ability of large general domain models to perform as well as, or even outperform, domain-specific models. This development has catalyzed significant AI activity in medical imaging, where otherwise it would be challenging to obtain sufficient annotated clinical images. For example, Inception-V3 serves as the basic foundation of many of the top medical imaging models currently published, ranging from ophthalmology, pathology to dermatology.
However, the proper development of clinical AI models requires significant time, resources, and more importantly, highly domain and problem-specific training data, all of which are in short supply in the world of healthcare. This is where LLMs like ChatGPT have the potential to make a significant impact. ChatGPT is a general model that can be trained on large amounts of text data, making it capable of generating novel sequences of words that represent plausible sequences based on natural human language. This means that it can be used in various industries, including healthcare, without the need for specialized training or reinforcement.
In conclusion, ChatGPT is a powerful AI model that has the potential to assist with medical education and possibly even clinical decision-making. However, more research and resources are needed to fully realize its potential in the healthcare industry. The healthcare industry has been slow to adopt the latest technology but it seems generative AI solutions like ChatGPT have caused a giant leap in healthcare solutions!
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