Design armored CAR-T cells with cytokine payloads and resistance mechanisms.
bio-longitudinal-monitoring
维护者 FreedomIntelligence · 最近更新 2026年4月1日
Tracks ctDNA dynamics over time for treatment response monitoring using serial liquid biopsy samples. Analyzes tumor fraction trends, mutation clearance kinetics, and defines molecular response criteria. Use when monitoring patients during therapy or detecting molecular relapse before clinical progression.
原始来源
FreedomIntelligence/OpenClaw-Medical-Skills
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-longitudinal-monitoring
- 维护者
- FreedomIntelligence
- 许可
- MIT
- 最近更新
- 2026年4月1日
技能摘要
来自 SKILL.md 的关键信息
核心说明
- Python:pandas + matplotlib ,用于 trend analysis 、 molecular response 分类。
- 跟踪 ctDNA levels over my patient's treatment" → Monitor tumor fraction 、 mutation dynamics across serial liquid biopsy timepoints ,用于 treatment response assessment 、 early relapse detection. Python:pandas + matplotlib ,用于 trend analysis 、 molecular response 分类。
- 跟踪 ctDNA dynamics over treatment ,用于 response assessment 、 relapse detection。
原始文档
SKILL.md 摘录
Clinical Integration
Goal: Generate a structured monitoring report combining tumor fraction dynamics, mutation clearance status, and molecular response classification for clinical decision support.
Approach: Aggregate tumor fraction trend analysis, mutation tracking pivot tables, and response criteria into a single report dictionary with standardized molecular response categories.
适用场景
- 适合在monitoring patients during therapy 或 detecting molecular relapse before clinical progression时使用。
不适用场景
- Do not rely on this catalog entry alone ,用于 installation 或 maintenance details。
上游相关技能
- ctdna-mutation-detection - Detect mutations to track
- tumor-fraction-estimation - Estimate tumor fraction per timepoint
- fragment-analysis - Complement with fragmentomics trends
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