AiAi.care project is teaching computers to "see" chest X-rays and interpret them how a human Radiologist would. We are using 700,000 Chest X-Rays + Deep Learning to build an FDA 💊 approved, open-source screening tool for Tuberculosis and Lung Cancer. After an MRMC clinical trial, AiAi CAD will be distributed for free to emerging nations, charita…

Profiling tool for Mycobacterium tuberculosis to detect ressistance and strain type from WGS data

MTBseq is an automated pipeline for mapping, variant calling and detection of resistance mediating and phylogenetic variants from illumina whole genome sequence data of Mycobacterium tuberculosis complex isolates.

A multivariate multi-step LSTM forecasting model for tuberculosis incidence with model explanation

vSNP -- validate SNPs

An R package for accessing and summarising the World Health Organisation Tuberculosis data.

Detecting tuberculosis from X-ray scan using pytorch

A snakemake workflow for WGS-based tuberculosis transmission analysis

A pipeline for comprehensive genomic analyses of Mycobacterium tuberculosis with a focus on clinical decision making as well as research

A pipeline for Bacterial Whole genome sequence data analysis

Profile RNA-seq data using published TB gene signatures

Benchmarking different ways of doing read (taxonomic) classification, with a focus on removal of contamination and MTB classification

PhD thesis submitted to the University of Bristol. Title: Modelling BCG vaccination in the UK: What is the impact of changing policy?

Mycobacterial pipeline

AiAi code-charity project for Cancer and Tuberculosis screening in Radiology Chest X-Rays (PA - CXR) using Deep Learning powered CAD algorithms. Come join our all-volunteer team to improve the healthcare in emerging nations!

Training AdaBoost Classifier of 500 estimators to classify HOG&LBP features of TB &NTB (Tuberculosis) chest X-ray images

Clinical Trial Risk Tool for analysing clinical trial protocols using natural language processing and assessing the risk of ending uninformatively, developed by Fast Data Science

A workflow for analysis and resistance profiling of Mycobacterium tuberculosis nanopore data with Mykrobe

MEDINFORM - AI Powered Multipurpose Web platform for Medical Image Analysis

10th place solution to the ImageCLEF Tuberculosis 2019 - Severity Scoring.