Alzheimer’s Disease (AD) is the most common neurodegenerative disease. It is typically late onset and can develop substantially before diagnosable symptoms appear. Electroencephalogram (EEG) could potentially serve as a noninvasive diagnostic tool for AD. Machine learning can be helpful in making inferences about changes in frequency bands in EEG data and how these changes relate to neural function. The EEG data was sourced from 2014 paper titled Alzheimer’s disease patients classification through EEG signals processing by Fiscon et al. There were patients with AD, mild cognitive impairment (MCI), and healthy controls. The data was already preprocessed using a fast fourier transform (FFT) to take the data from the time domain to the frequency domain. There were differing levels of effectiveness in terms of classification but generally, Fisher’s discriminant analysis (FDA), relevance vector machine, and random forest approaches were most successful. Due to inconsistent feature importances in different models, conclusions about important frequency bands for classification were not able to be made at this time. Similarly, different frequencies were not able to be localized to different regions of the brain. Further research is necessary to develop more interpretable models for classification.

an-embedded-platform-for-automated-patient-monitoring-system

an-incomplete-ml-paper-collection-for-biomedical-applications

This is a repository that collects machine learning papers on biomedical applications.

android-yolo-v2

Android YOLO real time object detection sample application with Tensorflow mobile.

antarctic_image_processing

Frame by frame analysis of a NASA video to collect information on the extent of sea ice in the Antarctic. Project for ELEC 221: Signals and Systems (Sep-Dec 2016).

aoslo-image-processing

This repository contains matlab software pertaining to automated photoreceptor segmentation in adaptive optics scanning light ophthalmoscope (AOSLO) images. The software was developed as part of our Biomedical Optics Express submission, titled "Unsupervised Identification of Cone Photoreceptors in Non-Confocal Adaptive Optics Scanning Light Ophthalmoscope Images".

arduino-signal-filtering-library

Arduino library for signal filtering

arduinoesp8266patientmonitor

Arduino Based Patient Monitoring Prototype with ESP8266 for Wifi Connectivity

array-representaion-using-numpy

visualization of 1D, 2D and 3D Array

artificial-intelligence-deep-learning-machine-learning-tutorials

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Automotives, Retail, Pharma, Medicine, Healthcare by Tarry Singh until at-least 2020 until he finishes his Ph.D. (which might end up being inter-stellar cosmic networks! Who knows! 😀)

assignment_01

First assignment for the Spring 2018 offering of Targeted Learning in Biomedical Big Data

astro250-python-computing

:school_satchel: Python for Data Science (Astronomy 250 seminar course at UC Berkeley)

atocha_vision

A selfdrving car video analysis script.

autodidactic_sandbox

This workspace contains interesting problems and solutions, models, visualisations, and other learning materials.

avalanche

Autonomous 6WD off-road survillance vehicle

awesome-computational-neuroscience

A list of schools and researchers in computational neuroscience

awesome-fuzzing

A curated list of fuzzing resources ( Books, courses - free and paid, videos, tools, tutorials and vulnerable applications to practice on ) for learning Fuzzing and initial phases of Exploit Development like root cause analysis.