Number of breast cancer histopathology diagnoses has considerably increased

EPOS focuses on AI diagnostics in Afghanistan
March 11, 2020

Over the past ten years, we have observed a dramatic shortage of qualified medical specialists in Afghanistan. While engaged in hospital renovation and construction in the northern part of the country, the lack of doctors who are able to diagnose non-communicable diseases (NCD) such as cancer became apparent: there are only eight pathologists nationwide, responsible for a population of nearly 32 million inhabitants. The low capacities for early stage disease diagnoses regularly result in high treatment costs and even in preventable deaths.

Women are particularly disadvantaged in seeking cancer diagnostic support and treatment in Afghanistan, as cultural restrictions prevent them from moving freely or from consulting a doctor on their own. Breast cancer is a nationwide concern with one in eight women suffering from the disease at a rather young age compared to Germany, statistically accompanied with high mortality rates.

Our  work in Afghanistan over the past decade was focused on piloting the use of telemedicin with a solution of artificial intelligence (AI) and deep learning added in 2019 for improved cancer diagnostics. We developed an integrated modular telemedicine solution that combines different medical cooperation interfaces via a multilingual electronic medical record (EMR) which has an expandable interface to AI diagnostic cancer cell interpretation. It further offers automated radiology and skin mole interpretation support.

With the support of integrated telemedicine and AI diagnostics, the number of breast cancer histopathology diagnoses has considerably increased, while the overall age of women seeking diagnoses has decreased from an average age of above 45 in 2009 to below 25 in 2019.

The benefits detected for of applying telemedicine with an AI interface for disease diagnosis include:

  • Doctors optimize their working time through faster and more accurate diagnoses, complemented by reliable artificial intelligence algorithms. This allows a) more patients to be diagnosed and eventually treated and b) doctors/specialists to focus on health care services such as advice and treatment.

  • Misdiagnoses by non-specialists decrease, thus reducing the number of unnecessary, missed or late applied interventions.

  • Inequalities in health are reduced. Smart solutions for distance support in healthcare provide remote rural communities with access to high quality health care services, which are usually only available in the main urban centers. Overall, access of patients to high quality services increases, promoting an inclusive approach which leaves less and less people behind.

  • In general, a higher number of suspected cancer cases can be diagnosed in the country itself, reducing the number of patients that travel to neighboring countries for diagnosis and treatment, linked to high costs which are only affordable to some parts of the population.

Many low to middle income developing countries are facing similar challenges of severe shortages of trained medical specialists, or suffer from restricted movement due to conflict, natural disasters, virus outbreaks or dangerous transportation infrastructure. They could benefit from an integrated solution of telemedicine and AI in a similar way.

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