Classification of AML/normal status of patients from flow cytometry

This solution template is meant to provide an alternative option to deploy machine learning models registered in AML workspace to AKS clusters.

The Drug Therapy Risk Prediction Accelerator is an end-to-end analytics platform that predicts the likelihood of a patient to experience a fatal adverse event (death) after receiving drug therapy. It was created for COVID-19 drugs but can be used for other prescription drugs.

Azure ML workspace with private endpoints

This repository contains the file codes used to complete the final project for the course Post Genomic Analysis.

DAR method - novel Adversarial machine learning defence

AML ML AI Statistics

Amulet Network Wiki (https://wiki.amulet.network)

Created an algorithm to identify metastatic cancer in small image patches taken from larger digital pathology scans. The data used for this competition is a slightly modified version of the PatchCamelyon (PCam) benchmark dataset (does not contain duplicates)

Amulet Network Docs (https://docs.amulet.network)

mvp project for graph analytics

Guidance for AML treatment at FHCC

The goal of the project is to predict AML or normal status of patients from flow cytometry data (single-cell). The samples were studied with flow cytometry to quantitate the expression of different protein markers. The challenge is to determine the state of health of the other half, based only on the provided flow cytometry data.

Here, we describe and provide an RNA-Seq analysis of a RIP assay to understand the mechanism of AML del(9q) progression. (Ali T. Abdallah)

Sirius.AI Research Programme (Spring 2024), DataBarrels Team. Blockchain AML.

Advanced Mobile Location SMS Parser

Analyses of Penter, Borji & Nagler et al., 2023