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A common assumption in medical AI research is that patient data is complete. A dataset might include imaging, clinical notes, lab results, and structured records, all neatly aligned for every patient.   Real hospitals rarely look like this.   In practice, patients often have entire categories of data missing. One patient might have fundus images but no clinical notes. Another might have detailed physician notes but no imaging. A third patient might only have lab results.   Th

When India’s Union Budget 2026 announced that healthcare spending had crossed ₹1 lakh crore, the number immediately took over headlines and timelines. It sounds historic, and in purely nominal terms, it is. A roughly 10% year-on-year increase signals that healthcare is no longer an afterthought in fiscal conversations. But big numbers in isolation rarely tell the full story, especially in public policy, where scale and context matter far more than symbolism. Once the initial