AlgoDx AB

Part of NIH Pavilion. AlgoDx is a medical device software company that develops clinically validated machine learning algorithms for autonomous disease prediction. The algorithms act as clinical decision support tools to empower clinicians to deliver personalized care and early clinical intervention. The aim is to improve patient outcomes across various clinical settings and reduce healthcare costs by providing accurate prediction, diagnosis, and treatment support.

AlgoDx is supported by Uppsala University in Sweden and Vinnova, Sweden innovation agency. AlgoDx has also established partnerships for the distribution of algorithms with leading electronic health record providers - Cambio Healthcare Systems and GE Healthcare.

Our Technology Offers

Sepsis Prediction Algorithm For Intensive Care

Sepsis is a severe life-threatening clinical syndrome caused by the dysregulated host response to infection. Annually, it affects 49 million people and accounts for 35% of hospital deaths. Despite being a potentially fatal condition, early intervention with antibiotics, fluid resuscitation, source control, and support of vital organ function have shown to dramatically improve patient outcomes. However, without any existing reliable biomarkers, early recognition of sepsis is a challenge. Recognition is further complicated by its syndromic nature and heterogeneity of the host response to infection. Although sepsis care bundles exist to guide rapid intervention upon sepsis recognition, early diagnosis or even prediction is vital in managing sepsis and patient outcome.

This technology offers a machine learning algorithm for autonomous sepsis prediction of intensive care unit (ICU) patients. It predicts sepsis onset in adult ICU patients up to 3 hours in advance, using clinical datapoints routinely collected in the ICUs. As a clinical decision support tool, sepsis prediction scores are calculated continuously and autonomously, alerting clinicians to patients at risk of sepsis development. The algorithm empowers clinicians to deliver personalized care and early clinical intervention. The aim is to improve patient outcomes and reduce healthcare costs by providing accurate prediction, diagnosis, and treatment support.

We are seeking partnerships with Electronic Healthcare Record (EHR) providers and healthcare organizations to integrate and test-bed the sepsis prediction algorithm. Other business opportunities and collaborative development of other disease prediction algorithms in intensive care (e.g. acute kidney injury, decompensation, cardiac arrest) are open to discussion as well.