โ†Boston NeuromindBoston Neuromind
๐Ÿง  DMDA ยท DSM5_TRํŒ๋ณ„ ์•Œ๊ณ ๋ฆฌ์ฆ˜DSM-5-TR Multi-Modal Diagnostic Algorithm
USPTO 6๋ฒˆ์งธ ํ›„๋ณด ยท Progressive Tier SystemUSPTO 6th Candidate ยท Progressive Tier System

DMDA ์ง„๋‹จ ํ—ˆ๋ธŒ DMDA Diagnostic Hub

์„ค๋ฌธ ยท ๋””์ง€ํ„ธ ๋ฐ”์ด์˜ค๋งˆ์ปค ยท qEEG ยท HRV ยท ERP ํŒ๋ณ„ ๋ถ„์„ Survey ยท digital biomarkers ยท qEEG ยท HRV ยท ERP multi-modal integration

๐Ÿš€ ์›Œํฌํ”Œ๋กœ์šฐWorkflow

1. ํด๋ผ์ด์–ธํŠธ ์ ‘์ˆ˜ โ†’ 2. ๊ฐ๊ด€ ๋ฐ์ดํ„ฐ ์ž…๋ ฅ (์„ ํƒ) โ†’ 3. Claude ๋ถ„์„ ์‹คํ–‰ โ†’ 4. ๋ฆฌํฌํŠธ 1. Client intake โ†’ 2. Objective data entry (optional) โ†’ 3. Run Claude analysis โ†’ 4. Report

๐Ÿ“
Intake (์ ‘์ˆ˜)Intake
90๋ฌธํ•ญ ์„ค๋ฌธ + ํƒ€์ดํ•‘ ๋™์—ญํ•™ + Tier ๋‹ค์ค‘ ์„ ํƒ 90-item survey + typing dynamics + multi-tier select
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๐Ÿ”ฌ
Engine (๋ถ„์„ ์—”์ง„)Engine
qEEG ๋‹ค๊ฐ๋„ ๋ถ„์„ + Claude AI + ๋‰ด๋กœํ”ผ๋“œ๋ฐฑ ํ”„๋กœํ† ์ฝœ qEEG multi-angle + Claude AI + neurofeedback protocols
โ†’
โšก
Objective DataObjective Data
qEEG ยท HRV ยท ERP ยท Face ยท Voice ์ธก์ •๊ฐ’ ์ž…๋ ฅ qEEG ยท HRV ยท ERP ยท Face ยท Voice biomarker entry
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๐Ÿ“Š
Reports (๋ฆฌํฌํŠธ)Reports
์ž„์ƒ ๋ฆฌํฌํŠธ ยท ์ข…๋‹จ ์ถ”์  ยท PDF ์ถœ๋ ฅ Clinical reports ยท longitudinal ยท PDF export
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๐ŸŽš๏ธ Progressive Tier ์‹œ์Šคํ…œProgressive Tier System

๋ฐ์ดํ„ฐ ์ˆ˜์ง‘ ๋‹จ๊ณ„๋ณ„๋กœ ์ง„๋‹จ ์ •๋ฐ€๋„๊ฐ€ ๋ˆ„์ ๋ฉ๋‹ˆ๋‹ค. ๊ฐ Tier์˜ ๋น„์ค‘์€ Admin์—์„œ ์กฐ์ • ๊ฐ€๋Šฅํ•ฉ๋‹ˆ๋‹ค. Diagnostic precision accumulates by data collection stage. Tier weights adjustable in Admin.

Tier 1 โ€” ์›๊ฒฉRemote +55%
์„ค๋ฌธ + ์‘๋‹ต ๋ฉ”ํƒ€ + ํƒ€์ดํ•‘ ๋™์—ญํ•™. ๋ณดํ—˜ ์—†์ด ์›๊ฒฉ ๊ฐ€๋Šฅ. Survey + response meta + typing dynamics. Remote, no insurance.
Tier 2 โ€” ์ž„์ƒClinical +20%
Tier 1 + qEEG. ๋ณดํ—˜ ์ฒญ๊ตฌ ๊ฐ€๋Šฅ. ์ž„์ƒ ํ‘œ์ค€. Tier 1 + qEEG. Insurance-eligible. Clinical standard.
Tier 3 โ€” ์ข…ํ•ฉComprehensive +15%
Tier 2 + HRV + Face + Voice. ์™„์ „ ๋‹ค์ค‘๋ชจ๋‹ฌ. Tier 2 + HRV + Face + Voice. Full multi-modal.
Tier 4 โ€” ์—ฐ๊ตฌResearch +10%
Tier 3 + ERP. ์ข…๋‹จ ์ถ”์  + FDA ์ง€์› ๋ฐ์ดํ„ฐ. Tier 3 + ERP. Longitudinal + FDA submission data.
โ€ป ๊ฐ€์ค‘์น˜๋Š” Boston Neuromind ๋‚ด๋ถ€ synthetic validation (N=1,000, Mean AUC=0.90) ๊ธฐ์ค€์ด๋ฉฐ ๋ฐ์ดํ„ฐ ๋ฒ”์œ„์ง€ ์ง„๋‹จ ์ •ํ™•๋„ promise๋Š” ์•„๋‹™๋‹ˆ๋‹ค. โ€ป Weights based on internal synthetic validation (N=1,000, Mean AUC=0.90); reflect data scope, not accuracy promise.