Big Data analytics in healthcare is a $30 billion industry. Therefore, big data plays a significant role in the healthcare industry. Over the last decade, there has been a rise in Korean big data startups in healthcare offering data-driven solutions for healthcare providers. They offer a wide range of data analytics and informatics tools in the healthcare sector. These tools can help organizations capture, manage, and analyze large volumes of data. Data can be collected in various ways thanks to the advancement of technology, such as e-medical records, tracking devices, and diagnostic systems. AI and ML can be applied to this data to identify critical patterns and correlations. It can also be vital for offering more personalized care for each patient. Big data and AI also play a significant role in genetics startups in Korea.
Below we listed some of the top Korean big data startups in Healthcare offering data-driven solutions.
Korean Big Data Startups in Healthcare
JNPMEDI
JNPMEDI is a medical data platform that is an all-in-one ecosystem that manages all aspects of digital clinical practices. They collect, monitor, and analyze medical data using blockchain and the cloud. They were able to raise $10 million for their Series A round.
AITRICS
Korean medical startup AITRICS provides AI-based healthcare solutions. They aim to make AI solutions accessible to all businesses for more predictive and personalized care. They are the developers of a predictive solution called VitalCare. It can predict the occurrence of emergencies related to sepsis and mortality in hospitals in advance. In addition, it provides accurate and predictive scores to help medical staff understand when and how to treat their patients properly. In addition, the medical startup has raised over $7 million from investors BNH Investment and Premier Partners, to name a few.
Life Semantics
Life Semantics is a Korean MedTech Tech startup that focuses on developing software platforms and systems for the medical industry. Their main outlet is called Life Record. It is a fully integrated information system. It provides healthcare organizations with the tools to improve hospital management, patient administration, and clinical tasks. Therefore, the platform integrates health record data from hospitals for their disease prognosis prediction algorithm. The data collected through their platform can provide vital information to set up a self-health management program and provide pre-emptive healthcare services.
Life Semantics is planning to launch a mobile solution that soon offers forecasting, prevention, and management of severe various disease outbreaks. Life Semantics got a $5.5 million investment from CareLabs back in 2018.
Deep Bio
Korean AI Biotech startup Deep Bio Inc. is focused on improving reliability and decreasing the turnaround time for medical diagnoses. Therefore, they collaborate with medical professionals in integrating AI into existing clinical workflows to help them make better-informed decisions based on data that will lead to the best patient outcome. Furthermore, Deep Bio has a team of medical experts and engineers to curate ideal datasets.
Their AI goes through many review cycles to establish the highest performance standard. Furthermore, it is seamlessly integrated into existing LIMS. In addition, it can be hosted on their DeepDx platform. Their first product was the DeepDx Prostate. It uses deep learning to recognize and localize acinar adenocarcinoma of the prostate in scanned, H&E-stained histopathology slides.
KaiPharm
Big data AI-based drug development startup KaiPharm is the developer of KMAP, a platform for analyzing drug-induced transcriptome data. Therefore, they can generate a dataset of 2,000 drugs using next-generation sequencing (NGS). The dataset will include all the FDA-approved drugs to date. In addition, they have raised over $5 million from KB Investment, Kolon Investment, and Innopolis Partners, to name a few.
linewalks
Korean big data startup linewalks provides AI-based software MDwalks for healthcare data management. It gives a view layer with a visualization engine optimized for healthcare data. It also includes chart graphs that can intuitively understand data, the combination of drugs and therapeutic materials and changes in patient status.
