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Created about 3 years ago
Updated about 3 years ago

sahikabetul

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⌚ DATA SCIENCE ⌚ Investigate the reason why some patients do not show up to their scheduled appointments and find the probability of missing the appointment ⌚

Motion-Compensated-Pulse-Rate-Estimation-by-Wearable-Device-Data

💓 WEARABLES 💓 Pulse rate estimation from PPG sensor data and 3D accelerometer data to avoid false high results from sudden movements 💓

Jupyter Notebook

Disaster-Response-Pipeline

📚 NATURAL LANGUAGE PROCESSING 📚 A simulation of pipelines: from data manipulation, model training with grid search and flask web app 📚

Python

Patient-Selection-for-Diabetes-Drug

💊 DATA SCIENCE 💊 Built a regression model that can predict the estimated hospitalization time for a patient and use this model to select/filter patients for the drug study 💊

HTML

Recommendations-for-Articles-on-the-IBM-Watson-Studio-Platform

📜 RECOMMENDATION ENGINE 📜 Putted my recommendation skills to use on real data from the IBM Watson Studio platform 📜

HTML

Stroke-Prediction

🧠 DATA SCIENCE 🧠 Understand what are the reasons that cause stroke to peoeple and see if we can succefully detect stroke on some features using ML technics 🧠

Jupyter Notebook

Hippocampal-Volume-Quantification-in-Alzheimer-s-Progression

🧠 3D MEDICAL IMAGE SEGMENTATION 🧠 FDA VALIDATION PLAN 🧠 Curate a dataset of brain MRIs, train a segmentation on a CNN, and integrate this into a clinical network to quantify hippocampal volume for Alzheimer's progression 🧠

Jupyter Notebook

Pneumonia-Detection-From-Chest-X-Rays-and-FDA-Submission

👩‍⚕️ 2D MEDICAL IMAGE CLASSIFICATION 👩‍⚕️ FDA SUBMISSION 👩‍⚕️ Analyze data from the NIH Chest X-ray Dataset and train a CNN to classify a given chest x-ray for the presence or absence of pneumonia 👩‍⚕️

Jupyter Notebook

sahikabetul/Medical-Appointment-NoShow-Prediction

sahikabetul

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