Project collaborations Digital Health, AI

KEYDATA offers a wide range of services including software development, network infrastructure, data center solutions, IoT, artificial intelligence. The company's goals are to grow in both local and global markets, especially by providing critical business applications in the healthcare and public sectors, as well as strengthening international collaborations by participating in European projects.

Our Products;

•        KeyHIMS is hospital information management system to use in hospitals  that covers both medical, financial administrative and back Office applications of a hospital. There is also a Mobile application so you may only use mobile phone to track patient records and examine their radyological imagery. 

•        Keydesk is an ERP solution and service desk software. KeyDesk includes all medical and performance parameters as per City Hospital contracts.

•        Keyos is a very useful, userfriendly interfaced operating system

•        KeyLMS is a remote learning management system that customer can make video lessons, quizes, exams and track them.

•        Keycloud is a cloud based file sharing system like onedrive.

The R&D team at KEYDATA conducts extensive research in the fields of artificial intelligence, deep learning, and machine learning. Our work, particularly focused on detecting anomalies in time series data, includes developing decision support solutions primarily for the healthcare and finance sectors. Currently, we are working on a TÜBİTAK-supported artificial intelligence project for the Ministry of Health, aimed at detecting anomalies in invoices issued by service providers.

We are currently involved in a horizon project called Climair, HORIZON-HLTH-2024-ENVHLTH-02-06-two-stage. The ClimAIr project will analyze data related to climate change, air pollution, and non-communicable respiratory diseases using artificial intelligence tools. These analyses will be used to develop better intervention methods and improve public health. Our task here is to develop artificial intelligence models using the Federated Learning (FL) method to protect patient privacy.