TY - JOUR
T1 - The future of mathematical oncology in the age of AI
AU - Rockne, Russell C.
AU - Andersen, Morten
AU - Anderson, Alexander R.A.
AU - Basanta, David
AU - Bentivegna, Angela
AU - Benzekry, Sebastien
AU - Branciamore, Sergio
AU - Brüningk, Sarah C.
AU - Conte, Martina
AU - Farahpour, Farnoush
AU - Karolak, Aleksandra
AU - Köhn-Luque, Alvaro
AU - Lorenzo, Guillermo
AU - Manookian, Babgen
AU - Rodin, Andrei S.
AU - Schmalenstroer, Lara
AU - Soler, Juan
AU - Tomasetti, Cristian
AU - Urbaniak, Konstancja
PY - 2026/1/26
Y1 - 2026/1/26
N2 - This perspective article discusses emerging advances at the interface of mechanistic modeling and data-driven machine learning, highlighting opportunities for AI to accelerate discovery, improve predictive modeling, and enhance clinical decision-making. We address critical limitations of current AI approaches and propose a perspective on a future where AI augments mechanistic rigor, clinical relevance, and human creativity under the umbrella of a redefined understanding of Mathematical Oncology.
AB - This perspective article discusses emerging advances at the interface of mechanistic modeling and data-driven machine learning, highlighting opportunities for AI to accelerate discovery, improve predictive modeling, and enhance clinical decision-making. We address critical limitations of current AI approaches and propose a perspective on a future where AI augments mechanistic rigor, clinical relevance, and human creativity under the umbrella of a redefined understanding of Mathematical Oncology.
U2 - 10.1038/s41540-026-00656-9
DO - 10.1038/s41540-026-00656-9
M3 - Review
C2 - 41588010
SN - 2056-7189
VL - 12
JO - npj Systems Biology and Applications
JF - npj Systems Biology and Applications
M1 - 22
ER -