The Role of ChatGPT in Reducing Storage, Energy, and Scalability Overheads in Blockchain-Based Healthcare Systems

Open artificial intelligence (A.I.) applications, including ChatGPT, are gaining recognition across diverse research domains, including healthcare, due to their effective handling of inquiries related to A.I. implementation in healthcare. Despite the growing use of blockchain technology in healthcare systems, existing research struggles with storage limitations, computational efficiency, and scalability issues. Therefore, an optimized approach is required to address these critical challenges, including ethical risks. This study explores the synergistic potential of ChatGPT's integration with blockchain technology. This study used a mixed methods approach. Content analysis was used to analyze the qualitative and quantitative data generated by the ChatGPT application. The Byte Pair Encoding (BPE) strategy is used to compress the proposed versions of smart contracts. Code metrics are used to evaluate original and compressed versions of smart contracts. The research identifies seven primary overhead challenges in BCT, with maintenance cost being a less-explored aspect. The BPE's compression results show that 23%–26% of data size was reduced in compressed smart contract versions. Moreover, the study's results show 32.5% and 35% performance improvement in two compressed versions of smart contracts, respectively. The study findings showed that ChatGPT removed the redundant checks by simplifying variable names and adjusting spacing for better smart contracts. Ethical implications are recognized, including privacy, biases, transparency, and academic integrity. ChatGPT demonstrates synergistic capabilities when integrated with BCT. The proposed research is better at overcoming overheads in blockchain-based healthcare systems than the existing works. ChatGPT holds promise in addressing overhead challenges in healthcare BCT. Its potential role in healthcare presents valuable applications to improve the efficiency and effectiveness of BCT in the healthcare domain.