We are experts in medical data

data science
data engineering
data integrations
artificial intelligence
machine learning
neural networks
natural language processing

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Veracell provides experts in data engineering and data science for healthcare and well-being.

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Trusted by operators in healthcare

We have already delivered dozens of solutions used by clinicians, researchers, nurses and healthcare providers. Trusted by the largest hospital district in Finland, as well as pharmaceutical companies, consultancies and health data providers, we guarantee a team with the experience for your success.

Our customers

Medical sciences and research

We provide missing expertise for research groups, in for example natural language processing (NLP) and machine learning. We deliver statistics, visualisations, and solutions for medical sciences.

Insurance companies

We deliver customer segmentation, predictive analytics, NLP solutions built on top of well designed data platforms and data architecture. We help in creating and improving data strategies and automating customer processes with the help of artificial intelligence.

Public services

We help with cloud migrations and the modernisation of IT solutions, building data integrations to collect data into single source platforms. Modern digital solutions enable efficient use of data for analytics and machine learning.

Healthcare services

We build data integrations between different systems, as well as data extractions and data mining. We have expert knowledge in survival and forecast models for identification of patient groups and risks. Healthcare ERP solutions help the customers to develop their own processes with data.

Our customers

Healthcare analytics

We have built data platforms for clinical data and offered helping hands for existing projects. We deliver data projects from proof of concepts to production installations with deep expertise in machine learning and AI.

Healthcare devices and technology

We have build data integrations to market-leading health devices and imported the data to different types of data platforms. We create forecasting models with time series data and develop analytics based on the data collected by medical devices.

Pharmaceutical wholesale

We can help with inventory management and sales forecasting with relevant experience from for example Amazon. We will build forecast models used by wholesale by importing more data from other sources.

Medical companies

We have helped study the effect of marketing and analysed drug effects based on real word data. We offer data science projects, where available data is used to answer for example marketing and sales questions that cannot be answered with existing BI reports.

Our data and AI solutions

Healthcare ERP for resource optimization

Design and data engineering for a healthcare ERP, used to improve the use of resources for more influential interventions.

Product design for athlete health data

Concept and user interface design for adding and displaying athlete health data.

Neural network based forecasting models

Machine learning and neural network based forecasting models for various healthcare applications.

Data exploration for medication advertisement

Data visualization to explore how medication advertisement affects clinicians' behaviour.

Implementation of healthcare analytics data platform

Architecture, infrastructure, and security development for a healthcare analytics data platform.

Natural language processing for patient journals

Natural language processing tools for automatic structuring and analysis of text materials.

Predicting the best response of current treatment lines

Predicting the best response of a patient that has multiple myeloma type of cancer.

Data explorer for clinical data

Cloud-enabled explorer for healthcare data to use by researchers, with easy-to-use interactive dashboard.

Integrations for IoT healthcare devices

Data models and data integrations for storing, processing, and utilizing IoT data for healthcare devices.

Analysis of microscopy images of human cancer cells

Quantitative analysis of microscopy images of human cancer cells using image recognition.

Identifying patients for cohort studies

Developed an AI model to extract information about tumor size and location, consciousness, and genetic alterations.

Anonymization of patient journals using neural masking

Hiding personal data in patient journals using neural masking.

Data pipeline implementation for patient data

Data is collected from a number of different source systems into a usable format.

UWB indoor location tracking for rehabilitation

Ultra-wideband and accelerometer data transfer for rehabilitation monitoring.

Improved SQL models for PowerBI reporting

Improved SQL data models for the client's healthcare products to meet the PowerBI reporting needs.

Read about our cases

Implementation of healthcare analytics data platform

We did application development, Azure cloud architecture and infrastructure, design and implementation of data integrations, and security development for a healthcare analytics data platform.

Healthcare ERP for resource optimization

Our specialists led service design and data engineering in the development of an ERP for healthcare domain. The product helps to better target treatments and improve the use of resources for more influential interventions.

Analysis of microscopy images of human cancer cells

We implemented quantitative analysis of fluorescence microscopy images of human cancer cells using image recognition.

Integrations for IoT healthcare devices

We implemented data models and data integrations for storing, processing, and utilizing IoT data for healthcare devices on a cloud platform. Our specialists also led the user interface and service design of the new product.

Data explorer for clinical data

We designed and implemented a data explorer for healthcare data to use by researchers. The browser-based application had extensive filtering and data exploring capabilities within an interactive, easy-to-use user interface.

Natural language processing for patient journals

We have developed several different natural language processing tools for automatic structuring and analysis of text materials for healthcare.

Identifying patients for cohort studies

We developed an AI model that learned to extract information about tumor size and location, level of consciousness, and genetic alterations. This information was applied to speed up cohort identification in neurological studies involving stroke and brain cancer patients.

Data pipeline implementation for patient data

We implemented data integrations and pipelines for gathering patient data from different source systems. The data is pushed into a single data platform, from which it can be effortlessly used in any number of applications.

Anonymization of patient journals using neural masking

We implemented anonymization of sensitive data, such as names and addresses, in patient journals using neural masking.

Predicting the best response of current treatment lines

We worked with predicting the best response of a patient that has multiple myeloma type of cancer, with respect to the current treatment lines. The aim of the project was to help the clinical personnel decide whether the treatment should be changed or not.

Data exploration for medication advertisement

We did data engineering and visualization with Plotly.JS to explore how medication advertisement affects clinicians' behaviour.

UWB indoor location tracking for rehabilitation

We implemented ultra-wideband and accelerometer data transfer. Data is used for rehabilitation monitoring in cloud-native applications. Our team developed the signal processing components, data integrations and data visualizations.

Neural network based forecasting models

We extracted information from several healthcare systems and built an AI model that learns to predict future risk of custody. We have implemented various healthcare applications using machine learning and neural network based forecasting.

Product design for athlete health data

We designed a modern web service for saving and displaying athlete health data, users being athletes, physicians and coaches. An interactive product concept prototype was created based on service blueprint and use cases. New brand and marketing assets were also part of the delivery.

Improved SQL models for PowerBI reporting

We improved SQL data models for the client's healthcare products to meet the PowerBI reporting needs. Data was run through a multi-stage pipeline and validated in data graphs.

Our public healthcare cases

AI Roots is a network that helps its customers succeed in data-related development projects. We are able to quickly provide the right specialists for demanding data and artificial intelligence projects.

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DataKIT develops services to support the marketing of pharmaceutical companies. During the project, we have delivered a web application designed and implemented from start to finish to be used by DataKIT's pilot customers.

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We have helped Tietoevry to come up with new business, designed services using user-oriented methods and provided experts to implement technical solutions in the area of healthcare.

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PIRKKO®, developed by Integritas, is an application that can be used to improve mental health work with current resources. Veracell is taking the PIRKKO® system to the next level.

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What our customers say

"Veracell is our long-term trusted partner and enables us to deliver more demanding projects that require data and artificial intelligence expertise."

- Ari Rantanen, Partner at AI Roots

"From Veracell we found a professional team that we had been looking for to advance our lifecycle modeling. The results of the project are promising and lead us towards a production solution."

- Tomi Krogerus, Senior Manager of Analytics and AI

“Veracell handled the data and AI strategy sprint professionally and efficiently, which resulted in concrete plans for choosing the direction of AI development.”

- Johannes Karjula, CEO of Trustmary

"Long-term cooperation with Veracell has yielded good results. Veracell is a reliable partner for us in the development of our data-centric solutions."

- Hannu Tissari, Head of Product Development, Tietoevry.

Get to know us

Data, AI and design professionals at your service

Daniel Ciovica
Data scientist

Exploratory analysis on a raw dataset of patients with multiple myeloma and comparing the efficacy of recorded available medical treatment lines, using logistic regression and random forest. Predictive analysis on patients with glioblastoma using deep learning.

Akseli Kelloniemi
Data scientist

Implemented data pipelines to collect, clean, standardize and store electric health records, with data modeling, pipeline management and monitoring. Built models for forecasting demand of certain medications.

Valtteri Haavisto
Data engineer

Working in data analytics enabling more effective use of resources in social and psychiatric care. Interested in combining machine learning models and health technology for patient care and decision-making assistants.

Tuukka Ruhanen
Data engineer

Studying biosignal processing and health informatics during future Master’s studies. Aims to help healthcare professionals in their work by providing them with decision support based on the analysis of healthcare data.

Vili Sipilä
Data engineer

Holds an MSc in Biomedical Engineering, majored in Health Technology and Informatics. Has created an algorithm for detecting falls in a home or hospital setting and worked in a healthcare data analytics customer project handling data loading and transformation.

Stanislav Muhametsin
Software developer

Worked at Tietoevry to build a modern healthcare analytics platform, responsible of application development, Azure cloud architecture and infrastructure, data integrations, and security.

Eetu Pursiainen
Data scientist

Experienced in text analytics and natural language processing. Has built predictive models for predicting mortality in traumatic brain injury patients, and data pipelines for EMR data to be used for research purposes.

Onni Mansikkamäki
Data engineer

Data engineer working with healthcare-related data integrations, analytics and visualisation. Has been developing an ERP system for targeting resources in psychiatric care.

Markus Räsänen
Medical advisor

Markus Räsänen is part of Veracell's expert network, which helps us acquire specialized expertise in various fields for projects if necessary. As a top expert in his field, Markus strengthens our expertise in the field of healthcare and medicine.

Eemeli Kallio
Hardware developer

Implementing data integrations for Withings devices to enable social and health care professionals to monitor individuals' well-being in real time. Currently uses Azure functions, combined with full-stack development.

Antti-Jussi Mäkipää
Software developer

Worked on data visualization on how drug advertisement affects clinicians' behavior, EKG analysis with Python for decision support in healthcare, and analysis of MRI images in Matlab. Also knowledgeable about standards and regulations in healthcare (MDR).

Hannes Järvinen
Software developer

Built integrations of health monitors and visualization of health-related time-series data. Proficient in user-management in multi-tenant applications, API design for data-retrieval and stream-analytics to enable real-time analytics.

Antti Larjo
CTO, data scientist

Years of experience in bioinformatics and statistical and data analyses in medical research. Has worked in several projects with EHR data processing and analysing as well as developed data pipelines for clinical patient record systems in cloud environments.

Sergei Häyrynen
COO, data engineer

Analyzed complex biological datasets in academia and a CRO. Developed neural network models for healthcare NLP and predictive analytics. Built data platforms and applications for healthcare data.

Timo Erkkilä
CEO, AI advisor & sales

Data scientist developing predictive modelling, segmentation, and natural language processing (NLP) algorithms and data pipelines for medical research. Strong understanding of statistical modelling and hypothesis testing frameworks using frequentist and Bayesian approaches.

Krista Mellin
Director, design & strategy

Lead designer for many healthcare-related products, including application for tumor board work, explorer for clinical data, and multiple electronic patient record systems. Expert in data visualisation and user-centered design for healthcare professionals.

45 publications
20+ years
25+ projects
2 PhDs
45 publications
20+ years
25+ projects
2 PhDs
45 publications
20+ years
25+ projects
2 PhDs

Contact us

Timo Erkkilä
CEO, AI advisor & sales
timo.erkkila@veracell.com
+358 44 3758 909
Book a meeting

Some of our publications...

Machine learning-based dynamic mortality prediction after traumatic brain injury
Graft Immune Cell Composition Associates with Clinical Outcome of Allogeneic Hematopoietic Stem Cell Transplantation in Patients with AML
Challenges and opportunities for strain verification by whole-genome sequencing
Abstract LB-173: DNA methylation analysis reveals epigenetic regulation of neural differentiation in AT/RTs
Integrative DNA methylation analysis of pediatric brain tumors reveals tumor type-specific developmental trajectories and epigenetic signatures of malignancy
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