Artificial intelligence (AI) in medicine has enormous potential to transform the way healthcare is delivered, and one of the main areas where AI has been used is in diagnostics. This can be particularly useful in cases where diagnosis can be difficult, such as in cases of rare diseases or conditions that have atypical symptoms.
Nowadays, when we talk about artificial intelligence, we can notice a much greater interest in the subject even from the most common people. Perhaps one of the reasons why this is happening is the arrival of a new AI tool called ChatGPT. With little running time, ChatGPT has conquered millions of users and generated some discussions, but its ability to establish a conversation from the processing of a huge volume of data and relying on thousands of examples of human language is something that in its overwhelming majority has positively surprised the people who use it, and which can even be used in the field of medicine.
Before we continue, we need to know: Do you already know the system for health clinics Ninsaúde Apolo? The Ninsaúde Apolo medical software has an agile and complete agenda, personalized electronic medical records for each specialty, and with legal validity, teleconsultation, financial control, health insurance billing, and much more. Schedule a demo or try the Ninsaúde Apolo medical clinic system right now!
Recently, ChatGPT got an update called Chat GPT-4, which is currently only available to ChatGPT PLUS subscribers. According to the company that created the GPT, OpenAI, the tool became "more creative and collaborative than ever", with the ability to "solve tough problems more accurately". In this new version of GPT, it is possible to read images, create recipes and even identify jokes. In addition, GPT-4 Chat is safer and more reliable, as it is 82% less likely to respond to requests for prohibited content and 40% more likely to produce factual answers compared to GPT-3.5.
As mentioned before, artificial intelligence in medicine has proven to be a very important tool, especially concerning diagnoses. With the use of algorithms and data analysis, it is possible to identify specific patterns and characteristics in medical images, laboratory tests, and medical histories of patients, assisting in the identification of diseases and in the appropriate treatment. In many cases, it has also proven efficient in identifying diseases such as breast cancer, melanoma, pneumonia, and even Covid-19. In addition, the technology can help predict the evolution of chronic diseases, such as diabetes and heart disease, allowing earlier and more effective treatment.
AI can be particularly useful in diagnosing rare diseases, which can be difficult to identify, as doctors may not have seen enough cases to recognize the patterns. AI algorithms can be trained on data from patients with rare diseases and compare it to data from patients without the disease, helping to identify characteristics that may be indicative of that pathology. Some examples of how artificial intelligence has been used in medical diagnosis include:
- Diagnosis by image: AI can be used to help interpret medical images such as X-rays, tomography, and magnetic resonance imaging. AI algorithms can analyze the images and identify suspicious or abnormal areas that could indicate the presence of a disease.
- Diagnosis based on symptoms: AI can also be used to help identify the underlying cause of symptoms that may be associated with various illnesses. AI algorithms can be fed information about a patient's symptoms and use that information to help identify potential underlying causes.
- Computer-aided diagnosis: AI can be used to help doctors make a more accurate diagnosis, providing additional information and suggestions based on clinical data. AI algorithms can analyze patient data and provide insight into possible causes of symptoms, helping clinicians make more informed decisions about diagnosis and treatment.
In other words, the use of artificial intelligence in health brings a great possibility of transforming the way medical diagnoses are made. In this context, the system for clinics Ninsaúde Apolo recently launched a tool that can serve as a second medical opinion during your appointments: the Houdini algorithm. When using it, the system can suggest requests for exams or possible diagnoses based on the patient's evolution.
Currently, it takes a medical professional an average of 8 interactions to arrive at a diagnosis. With that in mind, the Houdini algorithm was built, named after the greatest magician of all time, Harry Houdini, or as he is known worldwide, "The Great Houdini". To use it, after completing the patient's evolution by writing his symptoms and other information (which must reach a minimum of 280 characters), press on the ICD option. Then, you will have to press on the option "Surprise me", and then just wait for the "magic" to happen. The algorithm will read what has already been informed in that service and will suggest possible ICD codes to add to the history.
Usually, professionals in the area have already memorized many of the ICD codes used in their consultations, therefore they also usually remember their respective descriptions very well. However, as new cases arrive at your office, new disease classifications may be used, and if you are looking for an ICD code for the first time, this feature can help you find it faster.
The use of AI for diagnostics in medicine can also help reduce medical errors and increase diagnostic efficiency. In this sense, another advantage that Ninsaúde Apolo's Houdini algorithm could bring is a better use of medical time, as well as test requests that may be more assertive. Through the analysis of large volumes of data, technology can identify patterns that would be very difficult to be perceived by a human being, allowing a more accurate and faster diagnosis. Even so, it is important to emphasize that AI does not replace the work of doctors and health professionals, but it fulfills well the task of assisting in the process of diagnosis and treatment. In this context, the role of AI in healthcare is to provide valuable information for physicians and other professionals in the field to make more informed and accurate decisions.
Artificial intelligence in medicine can be useful not only concerning diagnoses but also in several other areas that make us reflect on the importance of AI in health. For example, after diagnosis, AI can be used to help determine the most effective treatment for a patient. AI algorithms can analyze data from previous treatments, as well as patient data to help predict which treatment will have the best outcome.
Artificial intelligence in healthcare can also be used to help medical research, analyzing large amounts of data to find patterns and trends. A good example of this is AI being used to analyze data from clinical trials, whose purpose is to identify which patients responded best to a specific treatment. Additionally, AI can be used to help manage patients by monitoring data such as heart rate, blood pressure, and blood sugar levels. AI algorithms can alert healthcare professionals if there is a significant change in any of this data, allowing them to take preventative measures.
So, did you like the tips? Keep following the blog for more content like this. Are you a healthcare professional but still don't use management software? Get to know the system for clinics Ninsaúde Apolo.
Written by Michele Martins
Translated by Karina Romão