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Intuitive Human-Artificial Intelligence Theranostic Complementarity
1Department of Nuclear Medicine, Fiona Stanley Fremantle Hospitals Group, The University of Western Australia, Murdoch, Australia.
Abstract:
Deep learning artificial intelligence (AI) algorithms are poised to subsume diagnostic imaging specialists in radiology and nuclear medicine, where radiomics can consistently outperform human analysis and reporting capability, and do it faster, with greater accuracy and reliability. However, claims made for generative AI in respect of decision-making in the clinical practice of theranostic nuclear medicine are highly contentious. Statistical computer algorithms cannot emulate human emotion, reason, instinct, intuition, or empathy. AI simulates intelligence without possessing it. AI has no understanding of the meaning of its outputs. The unique statistical probability attributes of large language models of AI must be complemented by the innate human intuitive capabilities of nuclear physicians who accept the responsibility and accountability for direct clinical care of each individual patient referred for theranostic management of specified cancers. Complementarity envisions synergistic engagement with AI radiomics, genomics, radiobiology, dosimetry, and data collation from multidimensional sources, including the electronic medical record, to enable the nuclear physician to spend informed face time with their patient. Together with physician discernment, application of the technical insights from AI will facilitate optimal formulation of a personalized precision theranostic strategy for empathic, efficacious, targeted treatment of the patient with cancer in accordance with their wishes.
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