Revolutionizing Healthcare with AI: Smarter Data Processing, Diagnostics, and Decision Making 

The MedTech World Dubai 2025 panel, “Revolutionizing Healthcare with AI: Smarter Data Processing, Diagnostics, and Decision Making,” brought together a distinguished group of experts to explore the transformative potential of AI in healthcare. Moderated by Dr. Justus Wolff, Manager at Syte, the discussion featured insights from Reenita Das, Healthcare and Life Sciences Partner & Senior Vice President, Frost & Sullivan; Dr. Khulood Alsayegh, Head of Clinical Standards & Guidelines, Dubai Health Authority; Dr. Sven Jansen, CEO, NeoQ; Michele Tarnow, CEO, Alliance Care Technologies; and Mathieu Lemay, CEO and Partner, Lemay Ai.

Addressing Bias in Healthcare Data 

Reenita Das underscored the gender disparity in clinical trials, highlighting how women, despite making up 51% of the population, are underrepresented in medical research. “We are only represented in 30% of clinical trials, making us invisible in many ways,” she stated. This lack of representation leads to biases in diagnosis and treatment, particularly in diseases like lung cancer, where women are diagnosed much later than men due to outdated risk assessment models. She emphasized that AI has the potential to bridge this gap by leveraging data for better risk screening and early intervention.

The Role of AI in Diagnostics 

Dr. Sven Jansen built on this discussion by pointing out the uneven distribution of AI applications in healthcare. “There are over 900 FDA-approved AI medical devices for radiology, yet only 40 for cardiology,” he noted. This discrepancy highlights how AI adoption varies across medical fields. He suggested that leveraging existing digital infrastructures, particularly in radiology and laboratory sciences, could accelerate AI’s effectiveness in diagnostics. He also emphasized AI’s role in training models using synthetic images, especially for rare diseases, which could improve diagnostic accuracy and accessibility.

AI’s Clinical Potential vs. Workflow Challenges 

Michele Tarnow provided a historical perspective on AI in healthcare, recounting how her company patented an AI-based differential diagnosis algorithm in 1998. While clinical AI tools have existed for decades, she argued that adoption has been slow due to workflow integration challenges and reimbursement structures. “We have over 62 AI algorithms for radiology and 50 for digital pathology, all FDA and CE approved. The real issue is changing the workflow and addressing capacity problems,” she explained. Tarnow pointed out that AI could mitigate the economic burden of diseases like glaucoma by facilitating early detection, yet current reimbursement models hinder its widespread implementation.

Ensuring AI’s Practicality for Physicians and Patients 

Dr. Khulood Alsayegh took a pragmatic approach, questioning whether AI tools are truly designed for their end users—physicians and patients. “Who is actually using these tools? Are they practical for physicians? Do patients feel safe with AI-driven decisions?” she asked. She also raised concerns about accountability, particularly in scenarios where AI plays a role in medical decision-making. “Is the physician verifying AI’s decision, or is AI verifying the physician’s choice?” she inquired. Dr. Alsayegh emphasized that the Dubai Health Authority is actively working to establish ethical AI frameworks to balance innovation with patient safety.

Building Trust in AI Systems 

Mathieu Lemay addressed the broader concept of trust in AI-driven healthcare. “Trust is more than just an F1 score; it involves robustness, reliability, resilience, controllability, explainability, predictability, transparency, and bias awareness,” he explained. He emphasized the importance of establishing clear engineering criteria to ensure AI’s reliability in clinical settings. Lemay’s approach called for a systematic methodology to assess AI’s performance and ensure its integration aligns with the existing doctor-patient trust model.

A Future Defined by Ethical and Practical AI 

The panelists collectively agreed that while AI holds immense promise, its success hinges on overcoming biases, improving clinical integration, addressing workflow disruptions, and fostering trust. Regulatory efforts, such as those being developed by the Dubai Health Authority, will play a crucial role in shaping AI’s trajectory in healthcare. As AI continues to evolve, collaboration between technologists, clinicians, and policymakers will be essential to ensure that innovation enhances patient care without compromising ethical standards. 

This engaging discussion at MedTech World Dubai 2025 provided a thought-provoking glimpse into the challenges and opportunities presented by AI in healthcare. The road ahead demands a balance between technological advancement and human-centric implementation, ensuring AI serves as a tool to empower, rather than replace, medical professionals and their patients. 

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