Any country's healthcare systems and institutions have their classifications applicable locally. Instead of a single united system, multiple vocabularies pose obstacles to patient data exchange, global healthcare big data analysis, and slow down research. So it is evident that researchers and healthcare providers lack a common medical vocabulary model that will meet all the requirements. One of our clients decided to create a comprehensive model representing the data from different sources and ontologies used in various fields of medical science and the healthcare industry. Check out how we contributed to this project!

Healthcare

Data Analytics

Data Science

We enhanced the leading European online learning platform with deep learning solution to ensure flawless customer experience. Majority of content watched online comes from recommendations: 80% on Netflix, and 60% on YouTube, as per the research (link to external resource). So one of the popular massive European online learning aggregating platforms opted for a robust recommendation and classification system. Read on to find out how we beat such challenges.

EdTech

Data Science

Machine Learning

We designed an ML-powered system for personified lab test results. It boosts the efficiency of physician office laboratories (POLs) and increases the speed of the medical service delivery system. Moreover, the system that we created became a part of a broader telemedical patient care delivery system. Read on to find out how we deal with challenges like this one.

Healthcare

Data Analytics

Data Science

Machine Learning

Computer Vision

Natural Language Processing

Since the time of Hippocrates clinicians all over the world strive to cure the patient, not the illness. Since a human is a highly organized creature with its features, everyone develops the disease and reacts to medical treatment differently. One of our clients decided to develop a treatment prediction solution based on personalized EHR/EMR data. Check out how our experienced team contributed to this project!

Healthcare

Data Analytics

Predictive analytics

Data Science

Machine Learning

Natural Language Processing

A modern approach to treatment, as well as medical research, requires a lot of data about a patient for a better outcome. More profound knowledge about the human body, genetic, phenotypic, or psychosocial characteristics could ensure precise identification of patient risk factors, early diagnosis of a disease, or treatment targeting. One of our clients decided to use medical data to build patient similarity networks to define the safety of hydroxychloroquine, a drug to treat rheumatoid arthritis. We determined whether it is safe to use hydroxychloroquine (alone and in combination with azithromycin) via building patient similarity networks.

Healthcare

Data Analytics

Predictive analytics

Data Science

Machine Learning

Natural Language Processing

Visualization of pathological processes plays a crucial role in establishing most clinical diagnoses. However, sometimes the results could be controversial. Various factors influence it: the quality of the equipment, lack of medical skills and knowledge, limited time, etc. One of our clients decided to develop an algorithm for a medical image segmentation solution to distinguish between normal and abnormal chest X-rays (CXR) images. Read on to find out details.

Healthcare

Data Analytics

Data Science

Machine Learning

Computer Vision

We created a marketing forecasting solution for real estate businesses increasing house sales 16,5 times per month. Check out how data science, predictive analytics, and targeted advertising made our client happy.

Data Analytics

Predictive analytics

Data Science

Machine Learning

We created the covid - 19 prediction tracker, calculating the risk of being infected and the potential number of patients contracted per precise location in Israel. Read on how we are contributing to the return to normality with pandemics growth curve modeling.

Healthcare

Data Analytics

Predictive analytics

Data Science

Machine Learning

Health data is becoming highly digested, and data science and predictive modeling enter the picture to facilitate precision oncology. One of our clients decided to turn tons of unstructured medical data into a predictive modeling solution for cancer progression. Since relying on seasoned professionals in medical data engineering, data analysis, and machine learning (ML) is crucial in this case, we took on a challenge. Read on to discover how we came up with a solution to cancer progression prediction for lung cancer and lymphoma patients.

Healthcare

Data Analytics

Predictive analytics

Data Science

Machine Learning