AlgoDx Raises 600 000 EUR in Seed Round to Develop Machine Learning Algorithm Diagnostics

AlgoDxStockholm-based AlgoDx, which focuses on supporting disease detection and prediction with machine learning algorithms, has closed a 6 MSEK (600 000 EUR) seed round led by Nascent Invest with participation from angel investors Fredrik Sjödin and Tomas Mora-Morrison, co-founder of Cambio Healthcare Systems.

AlgoDx's first product, ExPRESS, has been developed to autonomously predict sepsis in hospitalized patients using data from electronic healthcare records. Reliable early prediction can mean the difference between life and death for patients that develop sepsis but is today resource intensive for clinical staff.

"We invested in AlgoDx because we believe that the team has a strong competitive edge within machine learning and a profound understanding of the clinical validation required to bring products to market in areas with unmet medical need," says Erik Gozzi, CEO at Nascent Invest.

Founded in 2018, the company intends to use the new investment to further scale the clinical validation of ExPRESS to demonstrate the benefits of autonomous sepsis risk monitoring in patients being treated at Intensive Care Units.

"We are at the commencement of a new age where machine learning approaches will enable earlier and more accurate detection and prediction of disease. The founding team at AlgoDx understands that clinical rigor is essential in order to bring machine learning solutions to market with integrations into electronic healthcare record systems," says Tomas Mora-Morrison, who will also chair the company's new Board.

"This seed round will allow us to continue the clinical validation of our sepsis prediction algorithm as planned. We are very proud to be supported by investors with a commercial outlook and a long-term investment horizon," says David Becedas, CEO at AlgoDx.

For further information, please visit:
http://algodx.com

About Sepsis and ExPRESS (TM)

Sepsis can lead to multiple organ damage and is a potentially life-threatening condition that occurs when the body's response to fight an infection is out of balance. Sepsis affects more than 30 million people worldwide yearly, potentially leading to 6 million deaths. In sepsis treatment, the time factor is critical; where the cornerstones of intervention are early and appropriate antibiotics together with source control and fluid administration. Current detection methods for sepsis are incapable of early prediction. AlgoDx's solution lies in the deployment of the ML-based prediction algorithm ExPRESS that, using only parameters that are routinely collected on Electronic Health Records, accurately predicts sepsis in hospitalized patients several hours before sepsis criteria are met.

About AlgoDx

AlgoDx is a privately-owned company associated with Uppsala University. The company's research portfolio consists of algorithm diagnostics and AI solutions in areas with unmet medical need.

Most Popular Now

Unlocking the 10 Year Health Plan

The government's plan for the NHS is a huge document. Jane Stephenson, chief executive of SPARK TSL, argues the key to unlocking its digital ambitions is to consider what it...

Alcidion Grows Top Talent in the UK, wit…

Alcidion has today announced the addition of three new appointments to their UK-based team, with one internal promotion and two external recruits. Dr Paul Deffley has been announced as the...

AI can Find Cancer Pathologists Miss

Men assessed as healthy after a pathologist analyses their tissue sample may still have an early form of prostate cancer. Using AI, researchers at Uppsala University have been able to...

New Training Year Starts at Siemens Heal…

In September, 197 school graduates will start their vocational training or dual studies in Germany at Siemens Healthineers. 117 apprentices and 80 dual students will begin their careers at Siemens...

AI, Full Automation could Expand Artific…

Automated insulin delivery (AID) systems such as the UVA Health-developed artificial pancreas could help more type 1 diabetes patients if the devices become fully automated, according to a new review...

How AI could Speed the Development of RN…

Using artificial intelligence (AI), MIT researchers have come up with a new way to design nanoparticles that can more efficiently deliver RNA vaccines and other types of RNA therapies. After training...

MIT Researchers Use Generative AI to Des…

With help from artificial intelligence, MIT researchers have designed novel antibiotics that can combat two hard-to-treat infections: drug-resistant Neisseria gonorrhoeae and multi-drug-resistant Staphylococcus aureus (MRSA). Using generative AI algorithms, the research...

AI Hybrid Strategy Improves Mammogram In…

A hybrid reading strategy for screening mammography, developed by Dutch researchers and deployed retrospectively to more than 40,000 exams, reduced radiologist workload by 38% without changing recall or cancer detection...

Penn Developed AI Tools and Datasets Hel…

Doctors treating kidney disease have long depended on trial-and-error to find the best therapies for individual patients. Now, new artificial intelligence (AI) tools developed by researchers in the Perelman School...

Are You Eligible for a Clinical Trial? C…

A new study in the academic journal Machine Learning: Health discovers that ChatGPT can accelerate patient screening for clinical trials, showing promise in reducing delays and improving trial success rates. Researchers...

Global Study Reveals How Patients View M…

How physicians feel about artificial intelligence (AI) in medicine has been studied many times. But what do patients think? A team led by researchers at the Technical University of Munich...

New AI Tool Addresses Accuracy and Fairn…

A team of researchers at the Icahn School of Medicine at Mount Sinai has developed a new method to identify and reduce biases in datasets used to train machine-learning algorithms...