Dilemmas of the Use of Artificial Intelligence for the Diagnosis of Tumor Diseases
Abstract
Artificial intelligence (AI) has achieved clinical advances in the diagnosis of tumor diseases, such as the intraoperative diagnosis of gliomas using Raman imaging, which takes less than three minutes and has a 94.6% accuracy rate compared to 93.9% offered by traditional methods. The document compiles a systematic review following PRISMA criteria of up to 40 documents from the last 5 years (2020-2025), focusing on the collection and analysis of clinical data and ethical regulations. The results show that AI systematically reviewed skin cancer cases and found that explainability with AI exceeds sensitivity and specificity (81.1% and 86.1%) compared to 74.8% and 81.5% offered by specialists without AI, but IPC MCGN remains vulnerable to imaging bias. However, important ethical concerns arise, such as algorithmic opacity, demographic bias, patient autonomy and consent, as well as the legal burden on the attending physician. As part of the conclusions, it can be said that, while AI technologies improve tumor diagnosis within neurotherapy, their application must be balanced with ethical principles of equity, respect for human autonomy, transparency, and care for the individual, which will ensure their responsible integration into medical practice.
Keywords: imaging diagnosis; tumor diseases; neuroscience; ethics in the use of artificial intelligence; ethics in the use of AI for medical diagnosis; ethical use of artificial intelligence; diagnostic bias in AI.
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Copyright (c) 2026 Luis Orlando Albarracín Zambrano, Deneb Gabriela Morales Andino, Maybrith Akane Moscoso Estrella, Denisse Isabel Suaste Pazmiño
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