What Generative AI could do for patients and doctors

Recently, I have been using Perplexity for information gathering and I have found that it is faster and more accurate than traditional search engines or even new Bing when it comes to finding relevant information. Additionally, Perplexity offers different search modes that can be selected based on specific needs. This got me thinking about the potential applications of Perplexity’s technology in the medical field.

Patients can provide the system with their lab results and physical sensations to receive a preliminary diagnosis. Many people tend to describe their symptoms and search for them on search engines. Typically, search engines return a series of related posts or even diagnostic results based on keywords. However, these results are often inaccurate, leading patients to misunderstand their health conditions and potentially increasing their psychological burden.

By leveraging generative AI technology in healthcare, we can create a more accurate and personalized diagnostic tool for patients. AI-powered systems can evaluate patients’ lab results, symptoms, and medical history to provide a more precise and reliable diagnosis. This would not only help patients understand their health conditions better but also alleviate unnecessary stress and anxiety.

In addition, such systems could guide patients towards appropriate medical care, reducing the likelihood of self-diagnosing inaccurately or self-medicating dangerously. Furthermore, AI-driven diagnostic tools could lead to more efficient use of healthcare resources, benefiting both patients and medical professionals.

For doctors, it can sometimes be challenging to ask the right questions for further diagnosis. Some doctors may even have cognitive biases, leading to biased questions during consultations. I recently went to the hospital due to gallbladder spasms, and during the clinical examination, my temperature was found to be slightly high at 38.2°C. The doctor insisted that my fever was caused by gallbladder inflammation. Even though I provided evidence of an unusual throat sensation, dizziness, and elevated neutrophil levels, the doctor still believed in their initial judgment. In the end, it was discovered that the cause was a bacterial infection due to not wearing a mask in the hospital.

By leveraging big data and generative AI systems in healthcare, doctors can reduce the impact of their subjective biases on diagnoses. These systems can help identify potential diagnostic blind spots and provide a more comprehensive understanding of a patient’s condition. With access to a wealth of data and advanced analytics, doctors can make more informed decisions and avoid relying solely on their subjective opinions.

Incorporating AI in the diagnostic process can also help doctors ask more relevant and targeted questions, leading to a more efficient and accurate assessment of the patient’s condition. As a result, patients can receive better care, and doctors can improve their diagnostic accuracy, ultimately enhancing the overall quality of healthcare.