# Episode 24: Computer models, AI, and the challenge ovarian cancer (with Marilisa Cortesi)

Page: https://stenobird.com/podcast/the-digital-twin-theory-7076419/episode-24-computer-models-ai-and-the-challenge-ovarian-cancer-with-marilisa-cortesi
Text version: https://stenobird.com/podcast/the-digital-twin-theory-7076419/episode-24-computer-models-ai-and-the-challenge-ovarian-cancer-with-marilisa-cortesi.md
Podcast: [The Digital Twin Theory](https://stenobird.com/podcast/the-digital-twin-theory-7076419)
Published: 2026-06-26T14:18:34+00:00
Episode link: https://www.spreaker.com/episode/episode-24-computer-models-ai-and-the-challenge-ovarian-cancer-with-marilisa-cortesi--72647009
Audio file: https://api.spreaker.com/download/episode/72647009/interview_marilisa_cortesi_mixdown.mp3
Processing state: not_requested
JSON: https://stenobird.com/v1/public/podcasts/the-digital-twin-theory-7076419/episodes/episode-24-computer-models-ai-and-the-challenge-ovarian-cancer-with-marilisa-cortesi
Duration seconds: 1566

## Resource

Ovarian cancer remains one of the most complex and challenging cancers to understand and treat. But how can computational models, artificial intelligence, and in silico medicine help researchers and clinicians tackle this disease? In this episode of The Digital Twin Theory, host Davide Montesarchio speaks with Dr. Marilisa Cortesi , biomedical engineer, Marie Skłodowska-Curie Global Fellow, and Assistant Professor at the University of Bologna. Together, we discuss the clinical challenges of ovarian cancer, the integration of computational modelling and experimental research, and the growing role of AI in oncology. The conversation explores the promises and limitations of artificial intelligence, the ongoing debate around the "black box" problem, and the potential of digital twins and virtual patients to transform personalised cancer care. Join us for an insightful discussion on how engineering, biology, and medicine are converging to shape the future of cancer research.

## Actions

- request_transcript: `POST https://stenobird.com/v1/public/podcasts/the-digital-twin-theory-7076419/episodes/episode-24-computer-models-ai-and-the-challenge-ovarian-cancer-with-marilisa-cortesi/transcription-requests` — Idempotently request low-priority transcript generation for this episode.
- read_markdown: `GET https://stenobird.com/podcast/the-digital-twin-theory-7076419/episode-24-computer-models-ai-and-the-challenge-ovarian-cancer-with-marilisa-cortesi.md` — Read the agent-friendly Markdown representation of this episode resource.

A page view does not enqueue transcription. Agents should invoke `request_transcript` explicitly when they need this episode processed.

## Transcript

Full transcripts are not published on public pages unless there is a clear rights basis.