Detection of risk of AMR in Tuberculosis Using AI

Our deep learning system utilizes publicly accessible medical image data of tuberculosis to develop models that harness genomic information. This model provide tailored solutions for TB management and AMR analysis against bacterial infection. By using data, the model identifies risk detection of AMR in tuberculosis. Furthermore, it provides diagnostic insights."

Prof. Dr. Muhammad Asif 

Dean, FoCAS & FoBMS,

Sir Syed University of Engineering & Technology,

Karachi, Pakistan.

Tuberculosis (TB) remains a global health challenge, necessitating innovative approaches to enhance diagnosis, treatment, and patient outcomes. Antimicrobials are utilized in virtually all contemporary medical technology. AMR arises when the resistance genes in these microorganisms experience spontaneous mutations over a period. The identification of comparative genomic traits that demonstrate the occurrence of convergent evolution in genomes associated with resistance and growth in human is significant. The primary focus lies on the management of treatment and prevention. The distribution of TB will be modified by number of patient’s interactions, and prevention of resistance is the only solution. The issue of antimicrobial resistance will persist as a significant menace. 

The target audience for risk detection of antimicrobial resistance in tuberculosis typically includes healthcare professionals, researchers, policymakers, and public health organizations involved in tuberculosis control and management. This audience may also encompass clinicians, microbiologists, epidemiologists, and specialists in infectious diseases. Additionally, it could involve government health agencies, non-governmental organizations (NGOs), and international health organizations focused on combating tuberculosis and antimicrobial resistance

This project will be user friendly specially  for under developed countries like Pakistan where health conditions are always ignored.Tubercluosis is the one of the oldest disease reported in Pakistan still people couldn't get out of it due to antibiotics resistance as people mostly used antibiotics without doctor prescribtions against any infection even viral one, therefore becoming anti microbial resistant day by day ,mutation could be am other reason.however this project could be predict anti microbial resistance in human against bacteria asp in TB 

Our target population will be un previlleged people of Pakistan,after Covid 19 people dealing with different anti microbial resistance.Tuberclusis is a bacterial disease but could be lethal without treatment..creating models by AI will be the task for prediction 

It will be give 9/10

. prediction models accuracy as a large number of people affected by this bacteria and treatment showed resistance to medicine easily returned

It would be very successful Studies, there is a large area to work for rural areas people asp in Karachi Pakistan 

Firstly data is not available easily to train.

Secondly people not will to share their genetic data.

Financial issues regarding python trained team expenses are 

Untrained staff

Budget for new systems

Sequencing data

Awerness in public for data

Samples from hospitals

Aga Khan

ICCBS

NIBD