It’s astounding to see how far humanity has advanced. Recently, scientists synced a monkey’s brain to a computer for the first time. Whether we want to examine our vision, check blood pressure, or scan lungs - we do all of that with the help of technology. Whenever we visit a hospital, we see machines beeping and blinking all of them aiding in health management. It includes one of the most critical spheres of our lives - healthcare. Indeed, technologies are a game-changer as our lives have become much easier with the advancement of technology. Look at what we got today - we do shopping without leaving home, travel across the globe, and even manage businesses via gadgets. To read more of this series, please visit technologies have made a significant impact on our everyday life. Ultimately, however, the further advances of artificial intelligence are fascinating, and it will be interesting to see how large language models such as ChatGPT are implemented into all aspects of life, including the healthcare industry, in the near future. Accredited physicians must remain the primary decision-makers in a patient’s medical journey. There will be a temptation to allow chatbox systems a greater workload than they have proved they deserve. Thirdly, while the chatbox systems have the potential to create efficient healthcare workplaces, we must be vigilant to ensure that credentialed people remain employed at these workplaces to maintain a human connection with patients. The remaining inaccuracies could be detrimental to the patient's health, receiving false information about their potential condition. While a median accuracy score of 5.5 is impressive, it still falls short of a perfect score across the board. Secondly, there will be cases of misinformation and misdiagnosis. Any healthcare entity using a chatbox system must ensure protective measures are in place for its patients. There are ethical considerations to giving a computer program detailed medical information that could be hacked and stolen. However, we must note the drawbacks of relying on such technologies before we proceed with their incorporation.įirst is the question of privacy. With hundreds of millions of users, people could easily find out how to treat their symptoms, how to contact a physician, and so on. These include OneRemission, which helps cancer patients manage symptoms and side effects, and Ada Health, which assesses symptoms and creates personalized health information, among others.ĬhatGPT and similar large language models would be the next big step for artificial intelligence incorporating into the healthcare industry. Many healthcare chatbots using artificial intelligence already exist in the healthcare industry. The mean scores were 5.7 and 2.8.Īmong all 284 questions asked across the two chatbox platforms, the median accuracy score was 5.5, and the median completeness score was 3.0, suggesting the chatbox format is a potentially powerful tool given its prowess. Again, the resulting median accuracy was 6.0, and median completeness was 3.0. To further cement their findings, the researchers asked the GPT-4 another 60 questions related to ten common medical conditions. These results suggest an improved answer generation for GPT-4, as expected. The mean score for accuracy improved from 5.2 to 5.7, while the mean score for completeness improved from 2.6 to 2.8, as medians for both systems were 6.0 and 3.0, respectively. To test and evaluate the accuracy and completeness of GPT-4 as compared to GPT-3.5, researchers asked both systems 44 questions regarding melanoma and immunotherapy guidelines. Notably, 26 of the 26 answers improved in accuracy, with the median score for the group improving from 2.0 to 4.0. The 36 inaccurate answers receiving a score of 2.0 or lower on the accuracy scale were reevaluated 11 days later, using GPT-3.5 to evaluate improvement over time. The researchers note that accuracy and completeness correlated across difficulty and question type. Most responses (53.3%) were comprehensive to the question, whereas only 12.2% were incomplete. Roughly 8% of questions were completely incorrect, and most answers given an accuracy score of 2.0 or less were given to the most challenging questions. Of the 180 questions asked for GPT-3.5, 71 (39.4%) were completely accurate, and another 33 (18.3%) were nearly accurate.
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