AI in Healthcare: From Administrative Burden to Clinical Precision
Artificial intelligence is increasingly becoming a practical tool in healthcare and pharmaceuticals, helping organizations automate time-consuming processes, analyze large volumes of medical data, and support more informed decision-making. In an interview for Manager.bg, MY Synergy discusses how AI is moving beyond experimentation and delivering measurable value in real healthcare environments.
At MY Synergy, we work through a proven process that allows us to move rapidly and in a controlled manner from identifying business needs to delivering and implementing a working solution.
Mladen Georgiev, CTO of MY Synergy
According to the interview, one of the biggest opportunities lies in reducing the administrative workload for healthcare professionals. AI-powered solutions can process medical documentation, extract and structure information, automate workflows, and help organizations work more efficiently while allowing healthcare teams to focus more on patient care. In the pharmaceutical sector, AI is also accelerating drug development processes and improving the management of clinical trials.
The interview highlights that AI adoption in Bulgaria remains uneven, with larger organizations investing more actively, while many healthcare and pharmaceutical companies are still looking for practical and sustainable ways to begin their digital transformation journey.
We continue to work on the application of AI in healthcare for screening and early diagnosis, assessing the risk of chronic and metabolic diseases by using routine chest X-rays to identify imaging biomarkers.
Yordan Iliev, CEO of MY Synergy
Among the solutions attracting strong interest is MYclaim, an AI-powered platform that automates the processing of health insurance claims by reading medical documents, extracting key information, validating claims against policy rules, and significantly reducing manual work. MY Synergy also shares its ongoing work in AI-assisted screening and early risk assessment of chronic and metabolic diseases through the analysis of routine chest X-rays, supporting earlier intervention and more proactive healthcare.
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