Empowering cancer prevention with AI: unlocking new frontiers in prediction, diagnosis, and intervention

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 r...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Cancer causes & control 2024-12
Hauptverfasser: Dafni, Marianna-Foteini, Shih, Mohamed, Manoel, Agnes Zanotto, Yousif, Mohamed Yousif Elamin, Spathi, Stavroula, Harshal, Chorya, Bhatt, Gaurang, Chodnekar, Swarali Yatin, Chune, Nicholas Stam, Rasool, Warda, Umar, Tungki Pratama, Moustakas, Dimitrios C, Achkar, Robert, Kumar, Harendra, Naz, Suhaila, Acuña-Chavez, Luis M, Evgenikos, Konstantinos, Gulraiz, Shaina, Ali, Eslam Salih Musa, Elaagib, Amna, Uggh, Innocent H Peter
Format: Artikel
Sprache:eng
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung: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.
ISSN:0957-5243
1573-7225
1573-7225
DOI:10.1007/s10552-024-01942-9