This is a stress-relieving website project made for the hackathon Hackofiesta. This project is under the theme Healthcare.
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Updated
Jul 5, 2024 - HTML
This is a stress-relieving website project made for the hackathon Hackofiesta. This project is under the theme Healthcare.
🥉 (Bronze medal - 163rd place - Top 6%) Repository for the "APTOS 2019 Blindness Detection" Kaggle competition.
A reminder app which can store medicines for multiple users. Works totally offline without internet connection.
Awesome List of Digital and Computational Pathology Resources
EHR Management Using Blockchain
This project aims to develop D-App for managing healthcare records
This is an example to demonstrate Amazon SageMaker Data Wrangler capabilities. The workshop showcases entire ML workflow steps for Diabetic Patient Readmission Dataset from UCI.
uBER for AMbulance
A javascript module for setting up and configuring your SPA
Explore our open-source repository focused on healthcare machine learning. We've developed predictive models for cardiovascular disease, diabetes, breast cancer, and more. Our projects employ diverse machine learning algorithms and data science techniques, enhancing early detection, diagnosis, and patient outcomes.
A android app designed to assist the caregiver of the elderly in their work and in their self care
HearTrans is a Capstone Project. The web app is to help transgender, intersex, and gender nonconforming individuals to find medical providers and locations.
Machine Learning in Genomics and Healthcare (COMP 565) Project
Predict 42 common diseases based on any 5 prominent symptoms among the 132 common symptoms given in the dataset. Get to know if you are affected with Malaria using your red blood cell image, among two classes: Infected and Uninfected. Classify the brain MRI reports into 4 classes: Glioma, Meningioma, Pituitary and No-Tumour. Later Segment the br…
Welcome to the NACSCOP Data Collection Tools - Indicator Selection Model repository! This project aims to provide an unbiased approach to select the appropriate indicator for data collection and reporting during the transition period when two sets of tools are in use.
Liver Disease prediction using binary classification such as SVM, ANN, or Random Forest. Generate missing data using the MICE algorithm. Use SMOTE to oversample minority class to reduce biases towards majority class. ROC analysis and k-fold Cross-validation Hypothesis tests were done. Data Source: UCI Machine Learning Repository
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