post by Muhammad Suhaib Shahid (2020 cohort)
- Introduction to My Placement Experience
In the summer of 2024, I embarked on a placement with Haleon PLC in Nottingham, as part of my doctoral research with the Horizon Centre for Doctoral Training (CDT). The placement was an incredible opportunity to merge my interests in artificial intelligence (AI) and healthcare, specifically focusing on oral health. Over the course of three months, I engaged in two primary projects: conducting interviews with industry professionals about AI in oral healthcare and collecting dual-modal data involving MRI scans and facial video recordings. This placement not only enriched my research and contributed towards my thesis, but also provided valuable insights into the practical applications and challenges of integrating AI into healthcare.
- Part One: Exploring AI in Oral Healthcare Through Interviews
2.1 Initiating Conversations with Industry Experts
The first phase of my placement involved conducting in-depth interviews with professionals at Haleon PLC. The goal was to understand the current landscape, perceptions, and future possibilities of AI in oral healthcare. I interviewed eight participants from various departments, including Innovation, Regulatory Affairs, and Medical and Scientific Affairs. Each participant brought unique perspectives based on their roles within the company.
2.2 Key Themes and Insights
The interviews were structured around several key themes:
- Understanding of AI in Oral Healthcare: We discussed how AI is currently being utilised in dentistry and oral health, including diagnostic tools, patient engagement platforms, and personalised treatment planning.
- Ethical Considerations: Participants shared their thoughts on the ethical implications of AI, such as data privacy, patient consent, and algorithmic bias. These discussions highlighted the importance of transparency and trust in implementing AI solutions.
- Impact on Professional Roles: A significant topic was how AI might change the roles of dental professionals. While some saw AI as a tool to enhance efficiency and accuracy, others were cautious about over-reliance on technology.
- Optimism vs. Skepticism: The interviews revealed a mix of optimism and skepticism. While there was excitement about AI’s potential to revolutionise oral healthcare, concerns were raised about practical barriers and the readiness of the industry to adopt such technologies.
2.3 Analysing the Data
After conducting the interviews, I performed a thematic analysis to identify patterns and key insights. Using Excel, I organised the transcripts and coded the data, which allowed me to draw meaningful conclusions that would later inform my thesis. This process was invaluable in understanding the multifaceted views on AI within the industry and provided a solid foundation for further research.
- Part Two: MRI Data Collection for AI Modelling
3.1 The Need for Dual-Modal Data
The second part of my placement focused on collecting dual-modal data to advance AI modelling in speech and oral movements. The aim was to create a dataset that combined internal views of the vocal tract (using MRI scans) with external facial movements (captured through video recordings). This data is crucial for developing AI models that can predict internal articulatory configurations based on external facial cues—a concept with significant implications for non-invasive diagnostics in oral healthcare.
3.2 Data Collection Process in Nottingham
3.2.1 Methodology
In the initial ethics application, we aimed to recruit 30 participants for the study. Each participant would undergo two recording sessions at facilities in Nottingham:
- Session One: Participants were recorded speaking and chewing in front of a camera, capturing high-resolution videos of their facial movements as they articulated specific sentences.
- Session Two: The same participants repeated the sentences while undergoing MRI scans. This provided real-time images of their internal vocal tract movements corresponding to the facial videos.
We later found that the upright MRI machine would allow us to simultaneously record the face and the internal view. We subsequently focused our efforts on this approach and did not implement session one; for the placement, we focused on performing an initial pilot study to refine the protocol.
3.2.2 The Pilot Study with Multiple MRI Machines
The pilot study involved two participants using two different MRI machines:
- 1.5T Scanner: Offered a balance between image quality and participant comfort.
- 0.5T Upright Scanner: Allowed participants to speak in a more natural, upright position, improving comfort and potentially leading to more natural speech patterns.
3.3.1 Adapting Procedures for Each Machine
Each MRI machine had unique requirements. For instance, the upright scanner necessitated adjustments in our data collection protocol to accommodate the participants’ posture. We also shortened the sentences used during the pilot to reduce the time participants needed to speak while being scanned, minimising discomfort and movement artifacts.
The pilot study was instrumental in understanding how different MRI technologies could impact data quality and participant experience. It highlighted the importance of selecting appropriate equipment based on the research objectives and provided valuable lessons for future large-scale data collection efforts.
- Reflections on the Placement Experience
This placement was a unique opportunity to apply theoretical knowledge in a practical setting. Working with Haleon PLC allowed me to see firsthand how AI concepts could be translated into real-world applications, particularly in oral healthcare.
Throughout the placement, I was constantly mindful of ethical considerations, such as obtaining informed consent and ensuring data privacy. The experience underscored the complexities of implementing AI solutions in healthcare, where patient welfare and ethical integrity are paramount.
Collaborating with professionals from various disciplines enriched my understanding and expanded my professional network. It was inspiring to engage with individuals who are at the forefront of innovation in healthcare.
- Conclusion and Acknowledgments
My placement with Haleon PLC in Nottingham was a great experience that significantly contributed to my doctoral research. The combination of conducting interviews and collecting dual-modal MRI data provided a comprehensive perspective on the challenges and opportunities of integrating AI into oral healthcare.
I would like to extend my heartfelt thanks to the team at Haleon PLC for their support and collaboration. Special appreciation goes to the participants who generously contributed their time and insights. This experience has not only advanced my research but also solidified my commitment to contributing to the field of AI in healthcare.