Success is not about the smartest algorithm. It is about the smartest integration of a verified solution into a human environment.
#HealthcareAI #MedicalAI #TMCAISummit
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Aim to amplify human judgment, reduce cognitive load, and allow providers to operate at the top of their license.
#HealthcareAI #MedicalAI #TMCAISummit
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The goal is to uncover an unmet need that is urgent, actionable, and valuable enough to pay for. #HealthcareAI #MedicalAI #TMCAISummit
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Most medical AI fails because it solves a problem that doesn’t exist. Technical feasibility is easy; clinical viability is hard. #HealthcareAI #MedicalAI #TMCAISummit
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PR is survival: build tools to provide your users clarity for better judgment, not to replace human roles.
#HeatlhcareAI #MedicalAI #TMCAISummit
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The cost of disruption: lesson 1 - manage the disruptions, don’t just build it.
#HeatlhcareAI #MedicalAI #TMCAISummit
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Up next at the 2026 TMC AI Summit are a couple of presentations on Design Your Own AI Startup 101. #HeatlhcareAI #MedicalAI #TMCAISummit
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Even once we verify that data is sound, and we can integrate AI without negatively impacting workflows, we should ask: is it fair, is it transparent and is it accountable?
#HeatlhcareAI #MedicalAI #TMCAISummit
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What does the future of successful deployment look like? From a model to a living system. Essential artifacts to now include dataset documentation and more.
#HeatlhcareAI #MedicalAI #TMCAISummit
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Common AI Data Failure Modes…
Data leakage, shortcut learning, distribution shift, label noise & unclear accountability.
#HeatlhcareAI #MedicalAI #TMCAISummit
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Five Questions to decide AI data readiness…
1. Fit for purpose data
2. Label quality
3. Validation design
4. Robustness
5. Monitoring & drift
#HeatlhcareAI #MedicalAI #TMCAISummit
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MSBMI faculty member Xiaoqian Jiang, PhD, is speaking on Navigating Frontiers in AI for #Health. #HeatlhcareAI #MedicalAI #TMCAISummit
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The synthetic framework provides a scalable, privacy-safe, and clinically accurate alternative to scarce real-word data.
#HealthcareAI #MedicalAI #TMCAISummit
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Guided diffusion enables controllable PROTAC linker design. Ultimately, this shifts diffusion from lifecycle generation to clinically informed candidate design.
#HealthcareAI #MedicalAI #TMCAISummit
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Why SVDD works for PROTACs? Domain-specific constraints are added. Including connectivity gate, SÁ scorer and geometry (avoids unrealistic linkers.)
#HealthcareAI #MedicalAI #TMCAISummit
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Why PROTAC linker design is hard…disconnected & geometry doesn’t fit.
#HealthcareAI #MedicalAI #TMCAISummit
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Next presentation is on Inference-Time Guided Diffusion for PROTAC Linker Design. #HealthcareAI #MedicalAI #TMCAISummit
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Learning how to effectively use agents takes time and effort. Agents require a new way of thinking: don’t think agents as a new tool, rather, think of agents as new members of your team. #AIinHealthcare #MedicaAI #TMCAISummit
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Combating hallucinations with LinkML AI harnesses. LinkML is a modeling language suited for complex knowledge models. LinkML provides an agentic harness with multiple guardrails. #AIinHealthcare #MedicaAI #TMCAISummit
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