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Predicting stroke events during hospitalization using medical datasets and developing a decision support system for optimized treatment.

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Stroke Prediction in Hospitalized Patients

Delighted to share the outcome of my recent project undertaken during an intensive week-long "Practical Experience with Medical Datasets" course! Collaborated closely with @Shahar, we focused on developing a decision support system to predict stroke events during hospitalization, optimizing treatment and minimizing potential damage.

Within the course, we collaborated with dedication and enthusiasm, culminating in a two-day hackathon to refine our project. While we take pride in our hard work and accomplishments, we recognize that further efforts are needed to achieve the desired and sufficiently robust results in our model.

Utilizing the extensive MIMIC4 dataset, a comprehensive medical database, we implemented a retrospective surgical approach and employed a classification model driven by support vector machines (SVM). This interdisciplinary project combined elements of healthcare data analysis, machine learning techniques, stroke prevention, and medical research.

The utilization of advanced data analysis methods within the healthcare context holds immense potential for enhancing patient care and outcomes. #HealthcareData #MachineLearning #StrokePrevention #MedicalResearch #DataAnalysis

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Predicting stroke events during hospitalization using medical datasets and developing a decision support system for optimized treatment.

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