The MUHAS Emerging Technologies for Health (ETH) research and development laboratory is a facility that operates under the Biomedical Engineering unit, Physiology Department at MUHAS School of biomedical sciences. The lab is focus on research and development of healthcare solutions by using emerging technologies with the aim of improving patient care and outcomes. These technologies include Artificial Intelligence, Virtual reality, Augmented Reality, Blockchain etc.

The lab also serves as a learning and training environment in biomedical engineering and related fields by providing short trainings, workshops and mentorships.


To research and develop solutions for healthcare by using emerging technologies. Including Artificial Intelligence, Virtual reality, Augmented reality, Blockchain


Leading research and development laboratory for healthcare technologies in the country, region and on the continent.


Three members of the lab have PhD’s in Artificial Intelligence, Signal Processing and Mathematical modelling obtained from the UK, Norway and Japan. Currently other three members are pursuing their PhDs in the same fields in China and German.

The other four members have masters and degrees in Biomedical engineering, with other members having degrees in prosthetic and Orthotic.

Some of the researchers of this lab have won different awards and competitions including “The International Innovation Competition for Automation and UAV 2014”, a competition held in China and IEEE Outstanding Young Investigator Research Visit award. Researchers in this lab have published several papers in peer-reviewed journals including Nature and IEEE. Some of the published works have been featured in global media houses including Forbes and the BBC.
Here is the list of publications that researchers from our Lab have either led or participated in.


Artificial Intelligence in the early detection of Dilated Cardiomyopathy

Cardiovascular disease (CVD) is a leading cause of death globally, with dilated cardiomyopathy (DCM) being one of the most common types. DCM affects adults aged 20 to 60 and leads to heart failure due to the heart’s inability to supply enough blood. It can also cause irregular heartbeats, blood clots, or sudden death. Currently, DCM is diagnosed using echocardiograms, but it is difficult to distinguish primary idiopathic/non-ischemic DCM from ischemic or cardiomyopathy due to hypertensive heart disease or diabetic or valvular disease, as all present with a dilated heart.

To improve early detection, the Emerging Technologies for Health (ETH) and Jakaya Kikwete Cardiac Institute (JKCI) are collaborating to collect and annotate DCM echocardiography images and train an AI model for early detection of DCM. The model will classify images related to DCM and detect its associated cardiac features in near real-time. The final product will be deployed in a mini supercomputer for local application, considering internet challenges in Tanzania. The intellectual property will belong to both participating institutes, and research findings will be disseminated through paper publications, conferences, and workshops with stakeholders. This 18-month project aims to improve early detection and treatment of DCM.

COSTECH – Commission of Science and Technology

Artificial intelligence for early detection of breast cancer

Following cervical cancer, breast cancer is the second most common cancer and the second leading cause of cancer mortality among women in Tanzania, this is largely due the absence of screening programs and limited access to diagnosis. In this project, we are creating Artificial Intelligence based breast cancer diagnostic system using breast ultrasound and mammogram.

• Google
• IDRC Through Villgro Africa
• SIDA through MUHAS

WhatsApp Image 2023-04-19 at 11.57.29

Artificial Intelligence for screening of TB among people living with HIV
Tuberculosis (TB) is a serious and potentially life-threatening disease that can be particularly challenging for people living with human immunodeficiency virus (HIV). People with HIV are at a higher risk of developing TB, and TB can also accelerate the progression of HIV. Therefore, screening and treatment for TB are critical components of care for people living with HIV. At ETH, we are developing an Artificial Intelligence based tool for screening of TB among people living with HIV.

IDRC through HASH (Hub for Artificial Intelligence in Maternal, Sexual and Reproductive Health)


Determining Validity, Optimality and Feasibility of introducing Socio-Economic Status Assessment Questionnaire in Routine Immunization Services in Tanzania.

Virus Image: Electron microscopic image of rabies virus. Courtesy: U.S. Centers for Disease Control and Prevention / Dr. Fred Murphy
Virus Image: Electron microscopic image of rabies virus. Courtesy: U.S. Centers for Disease Control and Prevention / Dr. Fred Murphy

Artificial intelligence for Rabies screening and early prediction of its outbreak
In this project, we are using artificial intelligence (AI) to detect rabies epidemics which involves the application of machine learning algorithms and techniques to analyse and process data related to rabies outbreaks. The goal is to identify patterns and trends in the data that can help predict, monitor, and respond to rabies epidemics more effectively. This is a joint project between MUHAS and Ifakara Health Institute.

• Lacuna fund

  • Using Artificial Intelligence to tackle ‘infodemic’ in Tanzania.
  • Using Artificial Intelligence to tackle challenges of tourism in Zanzibar



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