Can GPT-4 Contribute to the Healthcare Industry Metamorphosis?

According to Accenture's projections, the implementation of AI applications can reduce annual healthcare costs by USD 150 billion in the US by 2026. AI Chatbots, which are gaining popularity, can do more than just chat. They can potentially combine language skills with image and video recognition. Consequently, the next generation of large language models (LLMs), such as GPT-4, trained in multiple modalities, can become versatile AI capable of performing various tasks. The year 2023 has already brought exciting developments in healthcare AI, and the future promises technological interventions that will revolutionize the healthcare and life sciences industries. 

ChatGPT – An introduction

ChatGPT is a new AI tool developed by OpenAI, launched in November 2022. It is an LLM designed to mimic human-like conversation and generate responses based on natural language process inputs. It offers intelligent, computer-generated conversations in response to user queries. OpenAI has released its advanced language model, GPT-4, for public use, but it can only be accessed by users who upgrade to ChatGPT Plus for a monthly fee of USD 20. The new model claims to be secure and more accurate than its predecessor, GPT-3.5, as it has been trained on larger datasets and comes with notable updates. The tool has gained widespread attention since its launch due to its impressive computing power and ability to offer interaction in a seemingly “intelligent” human-like conversation.

ChatGPT in Healthcare

Although Chat GPT has certain challenges, such as obtaining precise and current data as well as privacy and security concerns, it has the potential for numerous future applications in healthcare. Its application to enhance patient care and the healthcare system's efficacy in the future will be intriguing.

1. Personalized Treatment Planning: Healthcare providers can utilize GPT technology to develop personalized treatment plans for patients by examining their medical history, existing symptoms, and other relevant information. The GPT-powered system can analyze the data and create a unique treatment plan that considers the patient's specific requirements and preferences. This approach can be valuable for patients with complex or unusual illnesses that necessitate specialized attention. For example, the GPT system can propose a unique medication or therapy combination that is most likely to be beneficial for a particular patient based on their medical history and other factors. This strategy can aid in lowering the chances of adverse reactions or complications and ensuring that patients receive the most appropriate treatment for their individual needs.
2. Healthcare Process Automation: GPT technology has the potential to assist healthcare practitioners with routine responsibilities such as transcribing medical records and generating reports. It can be programmed to be precise and fast in this task. Healthcare professionals can automate these tasks and concentrate on more critical duties, such as patient care and treatments. This can also assist in minimizing errors in medical records, which can have severe consequences for patients.
3. Virtual Patient Assistant: GPT has shown promise in the field of medicine by facilitating the development of virtual assistants that can cater to individual patients' needs. These assistants leverage patients' medical history, present symptoms, and other pertinent factors to offer tailored recommendations and guidance. For instance, a virtual assistant may propose home remedies or nonprescription medications to alleviate a patient's flu symptoms or provide insights into managing chronic illnesses like diabetes. Additionally, GPT-driven chatbots could offer mental health support, generate personalized nutrition, and exercise plans for patients based on their unique goals and requirements. Patients can access these virtual assistants through various channels, such as apps, websites, or voice assistants like Amazon's Alexa or Google Assistant. It can be valuable for individuals who reside in rural areas or face obstacles in obtaining healthcare. This allows them to receive personalized advice without requiring an in-person consultation with a healthcare professional.

ChatGPT Substitutes

1. Google: Google has responded to Open AI's ChatGPT by launching MultiMedQA, which is specifically designed to answer medical queries. Google Research and DeepMind have also launched MedPaLM at the end of last year, an open-sourced LLM for medical purposes . MedPaLM includes datasets that cover a range of clinical topics, including a new dataset called HealthSearchQA, which features in frequently searched medical inquiries curated to improve its performance. The latest version MedPaLM 2 achieved an 85% accuracy rate in answering medical exam questions, an improvement of 18% over the previous version of Med-PaLM. Last month, Google introduced its Generative AI System, Bard which also has the potential to transform healthcare.
2. Meta: Meta AI combined natural language processing and strategic reasoning to create CICERO, which is the first AI agent capable of performing at a human level in the complex natural language game "Diplomacy." When pitted against humans on the website, the AI agent demonstrated its state-of-the-art performance by outscoring all other players' average scores by more than two to one. Moreover, it was ranked among the top 10% of players who participated in multiple games.
3. Microsoft: Prior to Google and Meta's entry into the AI-driven healthcare solutions, Microsoft has also been collaborating with the OpenAI to utilize GPT-3 in enhancing the efficiency of healthcare teams by facilitating collaboration among employees and clinicians. Moreover, Microsoft has collaborated with Novo Nordisk to develop an AI-based Chinese-speaking chatbot for patients with diabetes.

ChatGPT Limitations

The accuracy of GPT responses depends on the quality of prompts entered. Hence, though they are designed to "feel correct to humans," they may not always be right. If the user lacks knowledge in a specific area, the answer may be incorrect, and they may not realize it. Biased data used to train GPT can result in inaccurate responses. In some fields, such as medicine, data may be limited, and GPT may be unable to answer a few questions. Additionally, GPT's data is only accurate up to September 2021, and it does not use the internet.

The use of GPT in healthcare presents a potential challenge - the need for precise and current data. To offer dependable treatment plans and recommendations, GPT must have access to up-to-date and accurate medical information. To address this challenge, the data that GPT uses should be updated regularly and obtained from trustworthy sources. Privacy and security concerns should also be considered when utilizing GPT in healthcare due to the involvement of sensitive medical information. Measures such as secure data storage and encryption will be crucial to protect patient privacy and guarantee medical data security.

Despite these limitations, GPT has the potential to revolutionize medicine and healthcare and has already been applied in various areas.