Medical digital twins, which are potentially vital for personalized medicine, have become a
recent focus in medical research. Here we present an overview of the state of the art in …

The use of digital twins (DTs) has proliferated across various fields and industries, with a
recent surge in the healthcare sector. The concept of digital twin for health (DT4H) holds …

We are rapidly approaching a future in which cancer patient digital twins will reach their
potential to predict cancer prevention, diagnosis, and treatment in individual patients. This …

Despite the remarkable advances in cancer diagnosis, treatment, and management over the
past decade, malignant tumors remain a major public health problem. Further progress in …

Triple-negative breast cancer (TNBC) is persistently refractory to therapy, and methods to
improve targeting and evaluation of responses to therapy in this disease are needed. Here …

Radiopharmaceutical therapy (RPT) is a rapidly develo** field of nuclear medicine, with
several RPTs already well established in the treatment of several different types of cancers …

We develop a methodology to create data-driven predictive digital twins for optimal risk-
aware clinical decision-making. We illustrate the methodology as an enabler for an …

The pace of technological innovation over the past three decades has transformed the field
of radiotherapy into one of the most technologically intense disciplines in medicine …

Medical digital twins are computational models of human biology relevant to a given medical
condition, which are tailored to an individual patient, thereby predicting the course of …

Radiopharmaceutical therapy (RPT), with its targeted delivery of cytotoxic ionizing radiation,
demonstrates significant potential for treating a wide spectrum of malignancies, with …