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ai_md_assistant

AI MD Assistant is an LLM based MD Assistant trained on the Medical Dialog clinical conversational Data. Includes LLama 2 13B Chat model fine-tuning code on aws sagemaker from data pre-processing to deployment.

ai_sec_analyzer

amplify-nextjs-starter-app

This is a Next.js starter for building a fullstack app with AWS Amplify.

aws-saas-factory-serverless

bitcoin

Live bitcoin price visualization using Apache Spark, Matplotlib and MongoDB

cnn-braintumordetection

Experimental Deep Learning Brain Tumor MRI Detection and Classification Project. This is work in progress. Uses Image Pre-processing to hightlight features. Train and test 3 types (VGG14, InceptionV3, ResNet50) of Convolutional Neural Network Architectures and assess accuracy metrics of each type. New Section will apply CSPNet (Cross Stage Partial Networks, Jun-Wei Hsieh et. al.) to same Brain Tumor Data.

dotfiles

fhir

The LinuxForHealth FHIR® Server and related projects

fhir-typescript-models

TypeScript FHIR models generated from the model-info-parser utility

grok-1

Grok open release

hapi

HAPI FHIR Server With Sample Patients

hapi-fhir

🔥 HAPI FHIR - Java API for HL7 FHIR Clients and Servers

heartdiseaseneuralnet

Keras Deep Learning Model for Predicting Heart Disease based on a Synthesized Cleveland dataset (see https://github.com/alsabay/SynthHD) from http://archive.ics.uci.edu/ml/datasets/Heart+Disease

heartdiseaseprediction

Heart Disease Prediction - UCI Machine Learning Repository Heart Disease Data

kineticsculpture

Kinetic Sculpture Art inspired by "Breaking Waves" by Plebian Design and Hypersonic

md-transcript

AI Powered Medical Transcription

medplum

Medplum is a healthcare platform that helps you quickly develop high-quality compliant applications.

medrec

medrec, a simple medical record in Ethereum Blockchain with Encryption

next-auth-tutorial-with-nextjs

next-auth-tutorial-with-nextjs

selfportrait

smart-on-fhir-tutorial

SMART on FHIR developer tutorial

synthhd

Synthesizing medical data from real observation in order to anonymize and expand the volume for machine learning.

twitter

Read from twitter stream, store in mongodb then geo plot

typescript-fhir-types

Typescript / Javascript object model for FHIR standard

vector_db_recommender

The notebook showcases how to leverage Word2Vec embeddings, Faiss indexing, and user profiles to create a movie recommendation system with personalized recommendations. It demonstrates the power of vector databases and embeddings in making similarity-based recommendations efficiently.