Daily Newsletter

09 January 2024

Daily Newsletter

09 January 2024

Nuvilab offers nutrition management solution for Alexandra Hospital 

The solution employs an AI Food Scanner to analyse individual food intake and nutrients from each patient's meal tray.

January 08 2024

Nuvilab, a Food artificial intelligence (AI) company, is offering a nutrition management solution for inpatients at Alexandra Hospital in Singapore.  

The solution employs an AI Food Scanner to analyse individual food intake and nutrients from each patient's meal tray.  

During a seven-week pilot phase at Alexandra Hospital, the solution demonstrated an average accuracy of 95%, which is more than double the accuracy rate of manual recording. 

With each scan taking less than a second, it improves the efficiency of meal recording tasks for medical staff. 

Following the trial, Alexandra Hospital has formalised an agreement with Nuvilab to implement the solution for inpatient care.  

The hospital plans to expand its bed capacity from 300 to 1,400 beds by 2028, with the Nuvilab tool to be deployed for all these beds. 

In addition to inpatients, Nuvilab extends its healthcare services to other demographics requiring health management, including seniors and children.  

In South Korea, the company introduced 'Yum-yum Kids,' a service enhancing dietary habits and managing child nutrition, with recognition from the Minister of Science and ICT for supporting data-driven childcare policy. 

Furthermore, Nuvilab is addressing patients with type 2 diabetes through the development of a new mobile service.  

This service, set to debut at CES 2024, integrates advanced technologies such as Continuous Glucose Monitoring (CGM) and generative AI to regulate dietary habits and improve nutrition management for individuals with diabetes. 

Nuvilab CEO Dae-hoon Kim said: “The key to healthcare lies in managing dietary habits. We plan to continuously improve and strengthen our healthcare services to assist in personalised dietary management with our expertise in food data.” 

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