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

In the rapidly evolving healthcare industry, data plays a critical role in improving patient outcomes, optimizing operations, and enhancing overall healthcare delivery. AWS QuickSight, a robust business intelligence and data visualization tool offered by Amazon Web Services (AWS), has emerged as a transformative solution for healthcare organizations seeking to harness the power of data-driven insights.

In the recent decade, as people have moved away from desktops to mobile devices, their consumption patterns have undergone significant transformation. One of such changes is the boost of video consumption from smartphones, which prompted mobile video advertising. Today, by creating a video tailored for mobile devices and the behavior of mobile users, advertisers can now achieve successful performance. At the same time, though growing in popularity, videos become shorter: in 2016, the average video length was 13.14 minutes, in 2017 6.07 minutes, and in 2018 it shrank to 4.07 minutes. So how is it possible to cut videos maintaining the content significance, and adjusting it to the viewer’s preferences? The answer seems obvious: you need to make your videos shorter and more content-intensive. But the reality is not that straightforward: each platform requires its format, length, and size, so you end up creating tons of video materials.

Natural Language Processing (NLP) and Machine Learning (ML) are two of the most prominent forms of artificial intelligence today that have revolutionized countless industries. They exist in every industry that helps people interact with computers and make our communication with technologies more meaningful. For example, NLP can help make sense of unstructured or semi-structured data from various sources and formats. In this case study, we describe our approach to extracting fields from spec sheets for the manufacturing industry.

Machine Learning

Natural Language Processing

NLP

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