Empowering cancer prevention with AI: unlocking new frontiers in prediction, diagnosis, and intervention
- PMID: 39672997
- DOI: 10.1007/s10552-024-01942-9
Empowering cancer prevention with AI: unlocking new frontiers in prediction, diagnosis, and intervention
Abstract
Artificial intelligence is rapidly changing our world at an exponential rate and its transformative power has extensively reached important sectors like healthcare. In the fight against cancer, AI proved to be a novel and powerful tool, offering new hope for prevention and early detection. In this review, we will comprehensively explore the medical applications of AI, including early cancer detection through pathological and imaging analysis, risk stratification, patient triage, and the development of personalized prevention approaches. However, despite the successful impact AI has contributed to, we will also discuss the myriad of challenges that we have faced so far toward optimal AI implementation. There are problems when it comes to the best way in which we can use AI systemically. Having the correct data that can be understood easily must remain one of the most significant concerns in all its uses including sharing information. Another challenge that exists is how to interpret AI models because they are too complicated for people to follow through examples used in their developments which may affect trust, especially among medical professionals. Other considerations like data privacy, algorithm bias, and equitable access to AI tools have also arisen. Finally, we will evaluate possible future directions for this promising field that highlight AI's capacity to transform preventative cancer care.
Keywords: AI technology; Cancer diagnosis; Cancer prevention; Early detection.
© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.
Conflict of interest statement
Declarations. Conflict of interest: The authors declare no conflict of interest. Consent to participate: Informed consent was obtained from all individual participants included in the study. Consent to publish: Consent to publish has been received from all participants. Ethics approval: This is a literature review, no ethical approval is required.
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