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Baby-Cardiac-Arrest-Detection-Using-ML
June 22, 2025 – June 22, 2025
This project uses machine learning to predict early signs of cardiac arrest in newborn babies based on vital signs like heart rate and oxygen saturation. Models like Logistic Regression, SVM, Decision Trees, and Neural Networks are applied to improve early diagnosis and support neonatal care.
View ProjectCultural Fit Analysis
The candidate's project diversity, including a machine learning project and a personal portfolio, indicates a breadth of interest. However, the experience level is 0, and there are no explicit skills listed beyond those in projects. Alignment with a 'React Frontend Engineer' role is limited to basic web technologies (HTML, CSS, JavaScript, TypeScript) and lacks specific React experience. The cultural fit is moderately aligned due to the initiative shown in personal projects, but the direct relevance to the target role is low.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The psychometric test score is 0, providing no actionable insights.