ADMOX - Smart Medical Solutions

Our AI initiative is a project to enhance computed tomography (CT) in the diagnosis of COVID-19 by using artificial intelligence. The project group will create a deep learning model for automated detection and classification of COVID-19 on CT scans, and for assessing disease severity in patients by quantification of lung involvement.

Our imaging analytics engine will be further extended to uncover brain, lung, liver, cardiovascular and bone disease in CT scans, 40 different conditions in X-rays scans, and breast cancer in 2D mammograms. 

Our AI screening tool will

1. Help emerging nations overcome shortage of Radiologists by screening X-rays within 45 seconds of capture. 

2. Reduce or completely eliminate contact between medical health frontline workers (lacking efficient PPEs) and the Covid 19 infected patients. Thus offering more protection.

Why Tuberculosis Algorithm?

One in four people are exposed to M. Tuberculosis bacterium, but it does not become active TB unless mixed with malnutrition and overcrowding. These two factors have earned TB the nickname "disease of poverty". Emerging nations have 12x fewer Radiologists compared to developed world, so TB patients often remain undetected while continuing to spread the bacterium further through air (coughing, sneezing, spitting). 

Our TB screening tool will help emerging nations overcome shortage of Radiologists by screening X-rays within 45 seconds of capture. 

Why Lung Cancer Algorithm

71% of lung cancers detected in chest X-Rays were visible in retrospect on previous imaging studies. Furthermore, a 1999 NIH long-term study of American Radiologists found that 19% missed lung cancers present in current chest X-Rays. These numbers may be more stark for developing nations where X-Rays are read by Primary Care Physians (PCP) instead of Radiologists.

Herein lies a 5X life-saving opportunity for early detection: We propose that a Machine-Learning screening tool with class leading sensitivity and specificity can help reduce missed-diagnose opportunities, and as a result improve survival rates 5X through early detection.

There is an increasing interest in the role of imaging for diagnosis of COVID19. The infection causes a wide variety of imaging findings on CT scans, most typically ground-glass opacities and consolidations in the periphery of the lungs.

1. The sensitivity of chest CT to diagnose COVID-19 has been reported as high and can predate a positive viral laboratory test. Therefore, in endemic areas where the healthcare system is under pressure, hospitals with a high volume of admissions are using CT for rapid triage of patients with possible COVID-19 infection.

2. Chest CT has an important role in the assessment of COVID-19 patients with severe and worsening respiratory symptoms. Based on imaging, it can be evaluated how severely the lungs are affected, and how the patient’s disease is evolving, which is helpful in making treatment decisions.

3. There is an increasing awareness that lung abnormalities caused by COVID-19 can be found unexpectedly in CT examinations performed for other clinical indications, e.g. in patients without respiratory complaints.

AI helps in reducing the burden on clinicians. While a manual read of a CT scan can take up to 15 minutes, AI can analyze the images in 10 seconds.

In the initial stage of this technology, it is aimed at tackling the current COVID-19 pandemic in the low and middle income countries having minimum access to testing instruments. Our team already developed in parallel, algorithms in oncology for the early detection breast cancer for vulnerable women without access to radiotherapy. Osteoporosis Detection in Bone, which is prevalent in most rural areas in Africa. Prostate cancer grade assessment as well as tuberculosis detection. Most people in the low and middle income countries develop these diseases and die from it without earlier detection nor diagnosis.

 MIT Solve is seeking improved solutions and tech innovations that can slow and track the spread of an emerging outbreak developing low-cost rapid diagnostics, analyzing data that informs decision making, and providing tools that support and protect health workers.

Our AI based solutions is focused on a preventative and mitigation measures that  can strengthen the access of the LMICs to affordable primary healthcare systems as well as enhance disease surveillance systems.