合規、隱私、本地部署是硬約束。我們是醫學博士牽頭的團隊——這件事順理成章，不是獵奇。 Compliance, privacy, local deployment are hard constraints. We're led by a medical PhD. This isn't a stretch—it's the natural fit.
在你家樓下診所的那台伺服器上。隱私合規、低延遲需求、硬件成本下降三股力量共同推動這一去中心化路徑。患者數據上了雲端，就意味着離開了你的控制範圍。本地部署直接解了這個扣——數據全程不出院牆，用完就地銷燬。急診室、手術室、ICU 這些地方對延遲的容忍度是零。本地部署還有一個好處：斷網了照樣跑。 It's on the server in your neighborhood clinic. Three forces push toward decentralization: privacy compliance, low-latency requirements, declining hardware costs. The moment patient data hits the cloud, it leaves your control. Local deployment solves it cleanly—data stays inside the hospital walls. ER, OR, ICU have zero latency tolerance. And local deployment keeps running when the internet doesn't.
閲讀完整長文《醫療 AI 的未來不在雲端》→ Read full essay: Medical AI Isn't in the Cloud →
本地大模型 vs 雲端 API 的成本曲線、推理延遲、模型迭代頻率
Local LLM vs cloud API cost curve, inference latency, iteration cadence
HIPAA / GDPR / 數據出境 / 醫療器械分類規則
HIPAA / GDPR / data sovereignty / medical device classification
HIS / PACS / LIS 接口、臨牀路徑、電子病歷語義
HIS / PACS / LIS interfaces, care pathways, EHR semantics
醫生抗拒度、護士工作流嵌入度、患者接受度
Physician resistance, nursing workflow fit, patient acceptance
單科室試點 → 全院灰度 → 多院區擴展 → 持續驗證
Single-dept pilot → hospital rollout → multi-site → continuous validation
創始人 Roland Wayne 是昆士蘭大學醫學博士。Implementation Science 這門學科本身起源於醫學。Founder Roland Wayne holds a medical PhD from U. Queensland. Implementation Science was born in medicine.
異構算力調優、本地大模型、零信任接入、虛擬化平台。Bill Wang 牽頭交付。Heterogeneous compute, local LLM serving, zero-trust access, virtualization. Led by Bill Wang.
已為高校上線 PDF 翻譯、OCR、RAG 對話等六大 AI 模塊的文獻處理平台。Jimmy Cole 主導。Built academic doc-intelligence platform: PDF translation, OCR, RAG dialog. Led by Jimmy Cole.
基於科室 SOP 與既往病例的本地化診斷輔助。Local diagnostic assistance grounded in department SOPs and prior cases.
自由文本病歷自動結構化到標準本體（SNOMED CT / ICD-10）。Free-text EHR auto-mapped to standard ontologies (SNOMED CT / ICD-10).
PubMed / Cochrane 自動檢索、證據等級標註、綜述初稿。Auto PubMed / Cochrane retrieval, evidence grading, draft systematic review.
問診前信息蒐集，問診後隨訪建議。門診外的 AI 價值。Pre-visit info gathering, post-visit follow-up. AI value outside office hours.
具體醫療場景待 Roland 與潛在客戶討論後補充。Specific scenarios to be added based on client discussions.
