sahikabetul
ArtificiaI Intelligence & Machine Learning Engineer @Mayo AI Lab - Healthcare Solutions https://medium.com/@sahika.betul
Mayo ClinicRochester, MN
Pinned Repositories
Disaster-Response-Pipeline
π NATURAL LANGUAGE PROCESSING π A simulation of pipelines: from data manipulation, model training with grid search and flask web app π
Hippocampal-Volume-Quantification-in-Alzheimer-s-Progression
π§ 3D MEDICAL IMAGE SEGMENTATION π§ FDA VALIDATION PLAN π§ 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 π§
Motion-Compensated-Pulse-Rate-Estimation-by-Wearable-Device-Data
π WEARABLES π Pulse rate estimation from PPG sensor data and 3D accelerometer data to avoid false high results from sudden movements π
Pneumonia-Detection-From-Chest-X-Rays-and-FDA-Submission
π©ββοΈ 2D MEDICAL IMAGE CLASSIFICATION π©ββοΈ FDA SUBMISSION π©ββοΈ 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 π©ββοΈ
Recommendations-for-Articles-on-the-IBM-Watson-Studio-Platform
π RECOMMENDATION ENGINE π Putted my recommendation skills to use on real data from the IBM Watson Studio platform π
Stroke-Prediction
π§ DATA SCIENCE π§ Understand what are the reasons that cause stroke to peoeple and see if we can succefully detect stroke on some features using ML technics π§
sahikabetul's Repositories
sahikabetul/Motion-Compensated-Pulse-Rate-Estimation-by-Wearable-Device-Data
π WEARABLES π Pulse rate estimation from PPG sensor data and 3D accelerometer data to avoid false high results from sudden movements π
sahikabetul/course-collaboration-travel-plans
sahikabetul/Hippocampal-Volume-Quantification-in-Alzheimer-s-Progression
π§ 3D MEDICAL IMAGE SEGMENTATION π§ FDA VALIDATION PLAN π§ 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 π§
sahikabetul/Medical-Appointment-NoShow-Prediction
β DATA SCIENCE β Investigate the reason why some patients do not show up to their scheduled appointments and find the probability of missing the appointment β
sahikabetul/Patient-Selection-for-Diabetes-Drug
π DATA SCIENCE π 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 π
sahikabetul/Disaster-Response-Pipeline
π NATURAL LANGUAGE PROCESSING π A simulation of pipelines: from data manipulation, model training with grid search and flask web app π
sahikabetul/Pneumonia-Detection-From-Chest-X-Rays-and-FDA-Submission
π©ββοΈ 2D MEDICAL IMAGE CLASSIFICATION π©ββοΈ FDA SUBMISSION π©ββοΈ 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 π©ββοΈ
sahikabetul/Recommendations-for-Articles-on-the-IBM-Watson-Studio-Platform
π RECOMMENDATION ENGINE π Putted my recommendation skills to use on real data from the IBM Watson Studio platform π
sahikabetul/Route-Planner
π A* SEARCH ALGORITHM π Build a route-planning algorithm -like the one used in Google Maps- to calculate the shortest path between two points on a map π
sahikabetul/Stroke-Prediction
π§ DATA SCIENCE π§ Understand what are the reasons that cause stroke to peoeple and see if we can succefully detect stroke on some features using ML technics π§
sahikabetul/AI4DOCTORS
sahikabetul/Data-Structures-and-Algortihms
Udacity nanodegree program contents
sahikabetul/dsand-p0-investigating-texts-and-calls
sahikabetul/HackerRank-One-Week-Interview-Preparation-Kit
sahikabetul/Investigating-Texts-and-Calls
β± TIME COMPLEXITY ANALYSIS β± Use Python to analyze and answer questions about the texts and calls contained in the dataset. Then, perform run time analysis of the solution and determine its efficiency β±
sahikabetul/OpenAI-Gym-s-Taxi-v2-Task
πREINFORCEMENT LEARNINGπSolution of Taxi-v2 Task with Expected Sarsa methodπ
sahikabetul/sahikabetul
My personal repository
sahikabetul/stackoverflow
Findings from Stackoverflow 2017