Olivia Patel covers health, biotechnology, and scientific research in the age of AI. She holds a dual degree in biology and data science, and worked in a hospital research lab on risk prediction models before becoming a reporter. That background gives her a precise feel for regulatory constraints, biases in medical data, and the gap between "state-of-the-art" models and real clinical practice.

Olivia writes about diagnostic models, AI in medical imaging, generative models for drug discovery, and the quieter but critical work of using AI to optimize hospital operations and patient record management. She interrogates the reproducibility of studies, the failure modes of overfitted models, their impact on clinician workflows, and the thorny issue of accountability when a model makes a harmful error.

Her investigations test the rhetoric of "AI-powered medicine" against the realities of aging infrastructure, fragmented datasets, and unequal access to care. At AI-Telegraph, Olivia leads the "AI & Life Sciences" section, aimed at clinicians, researchers, medtech founders, and policymakers who want to distinguish genuinely transformative tools from conference-demo fodder. Her underlying stance is simple: AI will not save lives if it ignores the complexity of human biology and the institutions that deliver care.