Modified MobileNet-ShuffleNet-GhostNet Network for Lightweight Retinal Vessel Segmentation

Algorithm and application for the wearable stress measurement system developed for the EBME 380 senior design project.

Young In Jang, AI/ML Researcher-ing in Connecteve, Republic of Korea

This file include all my assignment in Biomedical Computing(5th Semester) in Biomedical Engineering Major at Universitas Airlangga, Surabaya

This repository contains the user interface and some configuration features for a biomedical rehabilitation device prototype. The Gui was developed using Qt and PyQt libraries, the data was store using Sequence Query Language - SQL.

This repository was designed for data quantification of the research of SIRT-1 over expression influence on myogenesis in tissue engineered skeletal muscle.

Code for a novel activity sensing device that uses optical infrared and inertial sensing technologies

Repository for ENSC 413 Deep Learning Class Term Project

Package for obtaining the referential signal from a set of unipolar iEEG data

Project that I did in university. After importing a DICOM format picture from hospital, program should find the contour of the bone and display it.

This project aims to improve the accuracy of blood pressure measurements using video-based heart rate monitoring and a calculation algorithm. The system utilizes facial tracking to detect and analyze heart rate data, which is then used to estimate blood pressure.

Repository for bachelor thesis on Automatic Multi-Modal Detection of Autonomic Arousals in Sleep. The thesis itself and all related data is confidential and thus not publicly available, but access to the thesis can be granted by sending a request to hello@nicklashansen.com.

This is a joint stress calculator for a lateral shoulder raise. It calculates specific stress values for both the deltoidal muscle group, as well as the glenohumeral joint.

Draw periodogram of real EEG data

EEG spectrum mean of 84 records

Biomedical Image Analysis with TensorFlow and DLTK

This repository contains the scripts for the ML-Trauma project of the McDevitt Lab at NYU.

This Python script is designed to provide detailed information on interactions between drugs and genes using the Sydney module for natural language processing and the Drug Gene Interaction Database (DGIdb) API. Users can input the names of three drugs separated by commas and receive information on the interactions with the corresponding genes.