Stroke Risk Screening Analysis
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Please install @user_bb47e3e3/stroke-risk-screening-analysis according to https://skillhub.cn/install/skillhub.md.
About this skill
Problem
Stroke risk can appear through subtle facial and constitutional signals that a single blood-pressure reading or routine lab value may miss. This skill combines facial images or video with optional physiological metrics to produce screening signals for high-risk states such as cerebral infarction or hemorrhage, suitable for generating structured risk reports in an agentic workflow.
Core capabilities and workflow
- Facial feature analysis: evaluates complexion, tongue appearance, and mouth posture described as TCM face and tongue signals.
- Risk grading: uses optional inputs such as blood pressure, fasting blood glucose, and total cholesterol to issue graded warnings.
- Advice generation: provides dietary and lifestyle guidance, plus a report link.
- Historical report lookup: uses
--listto query cloud-stored reports and render them as a Markdown table.
The typical flow is to provide a local path or --url, set --media-type, and run the skill script. User identity is handled internally and should not be requested from or exposed to the end user.
Boundaries
The output is a health-risk screening prompt, not a substitute for professional medical examination or diagnosis. Inputs should be clear MP4/AVI/MOV video or JPG/PNG/JPEG image files up to 10 MB; if a high-risk signal is reported, seek medical care promptly.
Use Cases
- In a health chatbot conversation, a user uploads a frontal facial video and needs a stroke risk screening report with medical guidance.
- Using optional metrics such as blood pressure, fasting glucose, and total cholesterol, flag high-risk stroke signals from a single facial image.
- When a user asks for historical stroke screening reports, read the cloud report list and render it as a Markdown table.
- In remote follow-up workflows, run risk screening from a remote video URL and save structured results for later review.
Best For
- Health app engineers: need to connect facial video, images, and vital metrics to a chat flow and generate structured risk reports.
- Chatbot product managers: need to configure screening intent triggers, attachment handling, and cloud historical report lookup.
- Primary care health advisors: need to turn screening results into report links and medical guidance to support referrals for high-risk users.
- Data integration developers: need to call the skill scripts and cloud APIs, then render historical lists as Markdown tables.
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