Plasma medicine: The era of artificial intelligence

Abstract

The current trends that incorporate artificial intelligence (AI) and medicine have created new opportunities for improvement in both early diagnosis and treatment of diseases. In this framework, AI might also have the potential to significantly revolutionize the way we approach the field of plasma medicine, an area that is quickly growing and uses cold atmospheric plasma (CAP) to address a variety of medical conditions. Plasma medicine offers promising therapeutic alternatives for conditions widely ranging from cancer treatment to wound healing and antimicrobial applications, but the complexity of the plasma sources and the huge number of parameters may be overwhelming for the determination of underlying mechanisms and for understanding the effect of the source. This is where AI steps in, to provide strong tools for modeling, evaluating, and controlling CAPs. By harnessing the power of AI, researchers in the plasma medicine area, are now able to evaluate massive volumes of data, enhance their treatment protocols, and predict treatment results with a level of precision never possible before. Hereby, we emphasized the potential and further utilization of AI in plasma medicine in light of the fascinating and recent developments in this cooperation. New opportunities are encouraging, but potential limitations, ethical issues, model transparency, and generalizability should be considered. Regardless, the possibilities are endless, and the future of plasma medicine is looking brighter than ever with the implementation of AI.

Personalized Plasma Medicine for Cancer: Transforming Treatment Strategies with Mathematical Modeling and Machine Learning Approaches

“…Advancing diagnostic tools, exploring new combination treatment strategies with CAP treatment, and modeling with advanced algorithms will pave the way for more precise and personalized plasma-based therapies. AI is transforming plasma medicine, improving treatments with precise models, data analysis, real-time diagnostics, and protocols, despite ethical and transparency concerns [86]. The ongoing advancements at the frontiers of plasma technology in oncology are poised to revolutionize cancer treatment paradigms, providing new hope and improved outcomes for cancer patients worldwide.…”

“…Notably, the integration of AI techniques holds promise for addressing these limitations by improving prediction accuracy, automating feature engineering, accommodating nonlinear relationships, handling noisy and incomplete data, enabling real-time adaptability, and incorporating diverse data types [84]. Mathematical modeling entails the creation of mathematical representations for real-world systems, while ML approaches use data-driven techniques to learn patterns and make predictions, often incorporating mathematical principles, formulas, and statistical methods within their frameworks [85,86]. By combining the strengths of mathematical modeling and ML, we can potentially offer improved patient care and treatment strategies [87], enhancing clinical trials and personalized medicine.…”

“…las, and statistical methods within their frameworks [85,86]. By combining the strengths of mathematical modeling and ML, we can potentially offer improved patient care and treatment strategies [87], enhancing clinical trials and personalized medicine.…”

Plasma Control: A Review of Developments and Applications of Plasma Medicine Control Mechanisms

“…Temperature measurements, deposited power, and OES during operation have been some of the first cases of successful implementations of measured outputs for controllers. Machine learning methods that haven't been implemented into real-time diagnostics, but have produced outcome parameters, are Fourier transform infrared spectroscopy (FTIR) measurements [122], fluid modelling, and substrate target feedback [123]. Each of these diagnostic methods have yet to be incorporated and tested in experimental applications.…”

Machine learning-aided evaluation of oxidative strength of cold atmospheric plasma-treated water

“…There are a growing number of studies on the use of ML in medicine, but the use of ML in plasma medicine is only recently on the rise. Although the literature is limited, it is expected that further studies will be conducted in this area [31]. Bonzanini et al used ML to measure plasma effects on biological surfaces and predict treatment outcomes [19].…”