Applications of large language models in cancer care: current evidence and future perspectives

The development of large language models (LLMs) is a recent success in the field of generative artificial intelligence (AI). They are computer models able to perform a wide range of natural language processing tasks, including content generation, question answering, or language translation. In recent months, a growing number of studies aimed to assess their potential applications in the field of medicine, including cancer care. In this mini review, we described the present published evidence for using LLMs in oncology. All the available studies assessed ChatGPT, an advanced language model developed by OpenAI, alone or compared to other LLMs, such as Google Bard, Chatsonic, and Perplexity. Although ChatGPT could provide adequate information on the screening or the management of specific solid tumors, it also demonstrated a significant error rate and a tendency toward providing obsolete data. Therefore, an accurate, expert-driven verification process remains mandatory to avoid the potential for misinformation and incorrect evidence. Overall, although this new generative AI-based technology has the potential to revolutionize the field of medicine, including that of cancer care, it will be necessary to develop rules to guide the application of these tools to maximize benefits and minimize risks

Vaping and lung cancer - a review of current data and recommendations.

OBJECTIVES: Lung cancer is the most common cause of cancer mortality worldwide and, while tobacco smoke remains the primary cause, there is increasing concern that vaping and E-cigarette use may also increase lung cancer risk. This review concentrates on the current data, scholarship and active foci of research regarding potential cancer risk and oncogenic mechanisms of vaping and lung cancer. MATERIALS AND METHODS: We performed a literature review of current and historical publications on lung cancer oncogenesis, vaping device/e-liquid contents and daughter products, molecular oncogenic mechanisms and the fundamental, potentially oncogenic, effects of electronic cigarette smoke/e-liquid products. RESULTS: E-cigarette devices and vaping fluids demonstrably contain a series of both definite and probable oncogens including nicotine derivatives (e.g. nitrosnornicotine, nitrosamine ketone), polycyclic aromatic hydrocarbons, heavy metals (including organometal compounds) and aldehydes/other complex organic compounds. These arise both as constituents of the e-liquid (with many aldehydes and other complex organics used as flavourings) and as a result of pyrolysis/complex organic reactions in the electronic cigarette device (including unequivocal carcinogens such as formaldehyde - formed from pyrolysis of glycerol). Various studies demonstrate in vitro transforming and cytotoxic activity of these derivatives. E-cigarette device use has been significantly increasing - particularly amongst the younger cohort and non-smokers; thus, this is an area of significant concern for the future. CONCLUSION: Although research remains somewhat equivocal, there is clear reason for concern regarding the potential oncogenicity of E-Cigarettes/E-Liquids with a strong basic and molecular science basis. Given lag times (extrapolating from tobacco smoke data) of perhaps 20 years, this may have significant future public health implications. Thus, the authors feel further study in this field is strongly warranted and consideration should be made for tighter control and regulation of these products