Dr Jacqueline Matthew January Seminar Series
December 17, 2025
We were pleased to welcome Dr Jacqueline Matthew - Clinical Research Fellow/Sonographer at King's College London - who delivered her talk “From Noise to Signal: A Clinical Researcher's Perspective on Translating Advances in Prenatal imaging into Practice"
as part of our Seminar Series.
Abstract: Over the past decade, machine learning approaches in prenatal imaging has advanced from exploratory academic prototypes to clinically usable, real-time tools, but the path between those two endpoints is rarely straightforward. In this talk, Jacqueline offered a clinical researcher’s perspective on translating biomedical engineering innovations into real-world impact, tracing the journey from the iFIND project’s early breakthroughs in automated fetal imaging to the creation of Fraiya, an AI-driven ultrasound platform now entering clinical deployment. She unpacked the technical, clinical, and regulatory hurdles that shape this trajectory: data acquisition at scale, annotation complexity, model robustness, pipeline optimisation for real-time use, clinical safety engineering, regulatory strategy, and integration with NHS digital ecosystems. Beyond the technical achievements, the session reflected honestly on the innovation “gaps” that researchers and engineers encounter when stepping into entrepreneurship. From productising research outputs, building 'with' clinicians and service users not just 'for' them, securing buy-in, navigating procurement, and proving value in operationally stretched healthcare services. The aim was to provide a pragmatic and motivating roadmap for researchers and innovators seeking to turn biomedical AI research into deployable, sustainable solutions in healthcare.
Seminar Series Event: “From Noise to Signal: A Clinical Researcher's Perspective on Translating Advances in Prenatal imaging into Practice.
Date and Time:
Thursday 22 January 2026, 15:00 – 16.00 hrs (GMT)
Location:
K39, King's Building, Strand Campus
Attendance: Mandatory for all DRIVE-Health students, therefore please accept the calendar invitation.
Registration:
Alumni and wider King's College London research community all welcome - please email drive-health-cdt@kcl.ac.uk to let us know if you would like to attend.
Biography
Jacqueline is a clinical academic, sonographer, and MedTech entrepreneur with over 20 years of experience in advancing pregnancy care through compassionate, technology-driven solutions. Specialising in ultrasound and fetal MRI, Jacqueline’s work focuses on leveraging cutting-edge imaging technologies to improve screening, diagnosis, and care for pregnant women.
With a PhD in advanced 3D ultrasound and fetal MRI, Jacqueline uses machine learning to refine diagnostic pathways, pushing the boundaries of what’s possible in prenatal care. As Clinical Lead and Chief Medical Officer at an early-stage health tech startup, she has been at the forefront of developing a real-time AI-powered pregnancy ultrasound platform, with ambitions to transform how scans are performed, enhancing diagnostic accuracy, and empowering healthcare professionals to deliver more informed and compassionate care.
Jacqueline’s work has earned her widespread recognition, including being named one of the inaugural winners of the NHS England CAHPO Gold Award for Excellence, which celebrates health professionals who exemplify exceptional contributions to healthcare and the NHS values.
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Bridging Academia and Industry: Turning Health Data into Health Solutions Please join us for the EPSRC DRIVE‑Health CDT Summer Symposium & Partner Showcase 2026 , a two‑day event dedicated to bridging academia and industry and accelerating the journey from health data research to real‑world solutions. This year’s theme, “Bridging Academia and Industry: Turning Health Data into Health Solutions", brings together our vibrant community of students, King’s academics, industry partners, clinicians and policymakers to explore how collaboration can unlock new insights, innovation and impact across health and care. Event details 📅 11 & 12 June 2026 📍 Science Gallery London, Guy’s Campus, King’s College London, Great Maze Pond, London SE1 9GU Timings: ⏰ 10:00–16:00 each day ☕ Refreshments available from 09:30 👉 Please be seated by 09:50 for a prompt 10:00 start Please secure your place here: Register Now Programme highlights KEYNOTE ✨ Dr Luis Garcia‑Gancedo , Executive Director & Head of Digital Medicine – Respiratory, Immunology & Inflammation, GSK INTERACTIVE DEBATE ✨ Student‑led interactive debate exploring AI within the context of the event theme: “Bridging Academia and Industry: Turning Health Data into Health Solutions.” PANEL DISCUSSION & POSTER JUDGING ✨ “What does industry actually need from health data PhDs - and how can industry partner with academia for maximum impact?” Panelists confirmed so far: Dr Laura Acqualagna , Director of AI/ML Engineering, GSK R&D Dr Chris Callaghan , Consultant Transplant Surgeon, Guy’s Hospital Dr Nina Sesto , CEO & Co‑Founder, MEGI Health Dr Srinivasan Vairavan , Director of Data Science & Digital Health, JNJ Innovative Medicine R&D, and Visiting Adjunct Faculty, King’s College London Dr Nicolas Huber , Director, King’s Innovation Catalyst PLUS ✨ Student lightning talks (across both days) ✨ 3‑minute Student Spotlight Slides (across both days) ✨ Poster showcase & networking session (Friday) ✨ Prizes for outstanding contributions (Friday) Please secure your place here: Register Now If you are no longer able to attend the event, please email drive-health-cdt@kcl.ac.uk so that we can reallocate to our waiting list.
We are looking forward to welcoming Professor Honghan Wu, Professor of Health Informatics and AI at the University of Glasgow, who will deliver his talk “Large language model and Radiology: how to facilitate human and AI collaboration? " as part of our Seminar Series. Abstract: In this upcoming talk, Professor Honghan Wu explores the essential shift from viewing AI as a potential replacement for radiologists to recognizing it as a critical collaborative partner. Moving beyond basic tasks like detection and triage, the presentation highlights how AI can address practical clinical "pain points," such as reducing automated protocoling time by up to 60% and decreasing the time spent communicating with providers and patients by 30%. Professor Wu will present recent research on using knowledge-retrieval and Large Language Models for clinical report error correction and generation. The session concludes with an examination of the real-world deployment lifecycle, discussing the challenges of monitoring the over 700 FDA-cleared radiology AI devices currently in practice Seminar Series Event : “Large language model and Radiology: how to facilitate human and AI collaboration?" Date and Time: Thursday 25 June 2026, 15:00 – 16.00 hrs (BST) Location: Large Committee Room, Hodgkin Building, Guy's Campus Attendance: Mandatory for all DRIVE-Health students; a calendar invitation has already been sent. Registration: Alumni and wider King's College London research community all welcome - please email drive-health-cdt@kcl.ac.uk to let us know if you would like to attend. Biography Honghan Wu is a Professor of Health Informatics and AI, based in the School of Health and Wellbeing of the University of Glasgow, where he leads the research theme of data science and AI. Prof Wu is a co-director of Health Data Research Scotland. He also is an honorary professor at Hong Kong University, an honorary associate professor at Institute of Health Informatics, UCL, and a former Turing Fellow of The Alan Turing Institute, UK's national institute for data science and artificial intelligence. Prof Wu holds a PhD in Computing Science. His current research focuses on machine learning, natural language processing, knowledge graph and their applications in medicine.
