Structured medical case presentation for clinical rounds, conferences, and documentation. Generates SOAP-format or narrative case reports with physiologically accurate vitals, labs, and evidence-based plans. Use when the brief mentions "case report", "case presentation", "SOAP note", "clinical case", "ward rounds", "case summary", or "patient presentation".
Annuaire de skills
Découvrez des skills réutilisables pour les AI agents.
Chaque recommandation reste clairement reliée à son dépôt, son audit et son chemin d’installation.
Résultats de recherche: chest-xray
Annuaire en anglais一款长亭自研的完善的安全评估工具,支持常见 web 安全问题扫描和自定义 poc | 使用之前务必先阅读文档
MedRAX: Medical Reasoning Agent for Chest X-ray - ICML 2025
We are building an open database of COVID-19 cases with chest X-ray or CT images.
Подробная инструкция (как в pdf, так и в md формате) о настройке своего совбственного Xray-VPS-сервера (с протоколом VLESS XTLS-Reality через панель 3x-ui), а также настройке клиентских приложений (ПК и телефон)
A Babashka CLI and Claude Code/Codex skill providing structural Clojure refactoring operations for coding agents.
The major reason for the death in worldwide is the heart disease in high and low developed countries. The data scientist uses distinctive machine learning techniques for modeling health diseases by using authentic dataset efficiently and accurately. The medical analysts are needy for the models or systems to predict the disease in patients before the strike. High cholesterol, unhealthy diet, harmful use of alcohol, high sugar levels, high blood pressure, and smoking are the main symptoms of chances of the heart attack in humans. Data Science is an advanced and enhanced method for the analysis and encapsulation of useful information. The attributes and variable in the dataset discover an unknown and future state of the model using prediction in machine learning. Chest pain, blood pressure, cholesterol, blood sugar, family history of heart disease, obesity, and physical inactivity are the chances that influence the possibility of heart diseases. This project emphasizes to evaluate different algorithms for the diagnosis of heart disease with better accuracies by using the patient’s data set because predictions and descriptions are fundamental objectives of machine learning. Each procedure has unique perspective for the modeling objectives. Algorithms have been implemented for the prediction of heart disease with our Heart patient data set