Ram Sivaraman: HM-Detect: AI Detection and Classification of Heart Murmurs
HM-Detect: AI Detection and Classification of Heart Murmurs.
Ram Sivaraman developed HM-Detect, a methodology for detecting and classifying heart murmurs from multimodal signals using a novel neural-network architecture. Earlier, more consistent identification could help clinicians decide which patients need additional cardiac assessment, although medical use would require rigorous clinical validation.
Innovation mindset: Listen for subtle patterns that humans may interpret differently, then combine signals to improve consistency rather than relying on one data stream.
Official project title: HM-Detect: Murmur Detection and Classification Methodology Using A Novel C^2-LSTM Architecture for Multi-Modal Signals (Systems Software).
IP note
No public IP record; any filing made around the May 2025 fair would not yet be published under the 18-month rule — register check due from late 2026.
Recognition
Regeneron ISEF 2025 — First Award ($6,000).
What this means for a student inventor in India
[Editor: 120–200 words connecting this story to the Indian route — Section 6 (any true inventor may apply), provisional vs complete specification, disclosure at fairs (Section 31), renewals, and who owns what when a school is involved. Link to the relevant MYCrave guide.]
Related young innovators
- Trisha Prabhu — ReThink
- Nick D'Aloisio — Summly
- Nilay Kulkarni — Ashioto
Sources
[Editor: list the 2–4 primary sources from the research notes for this entry, with the date checked.]
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