Data Scientist & Machine Learning(ML) Specialist
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Master’s degree in computer science with two years of experience as a data engineer. Used Structured Query Language(SQL)/Python to perform extracting, transforming, and loading data(ETL) on large data sets. Worked towards enhancing surgical simulation in the medical field using data science and ML.
Florida Polytechnic University
Florida Polytechnic University
We classified the four different stomach parts manipulated during the ESG procedure with 97% training accuracy and classified two repeated tasks with 99% training accuracy with images. We also classified the four parts of the stomach with a 99% training accuracy and two repeated tasks with a 100% training accuracy with video frames...
Read MoreThis paper shows that feature reduction, in combination with classification algorithms such as SVM and KNN, can be used in tandem to classify endoscopists as experts or novices based on their results recorded using our grading metrics. Furthermore, this work introduces a non-linear constraint optimization to separate the two clusters and find the most important tasks using weights.
Read MoreWe had 2 classes: NICE 1 and NICE 2, and a total of 171 high-quality colorectal tumor images. We performed a comparison study about the classification of the colorectal tumor images according to NICE classification by using deep learning models between GoogLeNet, AlexNet, and InceptionV3. Our results show that InceptionV3 has better accuracy with an average of 92.39%...
Read MoreShoulder Arthroscopy is an operation for the treatment of tears on the shoulder. While this surgery is very common, there is no objective assessment for classifying expert surgeons from novice surgeons. Furthermore, cleaning of the tear’s region is the most important phase for the surgery. Therefore, our study focused on two tools which are used to perform this phase...
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