Towards AI-Based Precision Oncology: A Machine Learning Framework for Personalized Counterfactual Treatment Suggestions based on Multi-Omics Data

arXiv:2402.12190v1 Announce Type: cross
Abstract: AI-driven precision oncology has the transformative potential to reshape cancer treatment by leveraging the power of AI models to analyze the interaction between complex patient characteristics and their corresponding treatment outcomes. New technological platforms have facilitated the timely acquisition of multimodal data on tumor biology at an unprecedented resolution, such as single-cell multi-omics data, making this quality and quantity of data available for data-driven improved clinical decision-making. In this work, we propose a modular machine …

abstract ai models analyze arxiv cancer cancer treatment counterfactual cs.lg data framework machine machine learning oncology patient personalized platforms power precision q-bio.qm reshape stat.ml suggestions treatment type