Read our blog and carry on

Ever wonder why so many machine learning (ML) models never see the light of day? Despite their huge potential, only 32% of data scientists say their models usually get deployed. Even more shocking, 43% report that 80% or more of their models never make it into production. This means many businesses miss out on the full value of their AI projects. Imagine a retail company spending months developing a sophisticated customer recommendation system, only for it to never be implemented—losing out on p

Healthcare providers manage an enormous volume of data daily, approximately 137 terabytes, most of which is unstructured. This includes a wide array of formats such as medical images, clinical notes, and genetic test results. Unstructured data, crucial for patient care, poses significant challenges due to its complexity and the varied sizes of its components. The volume of healthcare data is rapidly increasing, fueled by the widespread adoption of electronic health records and advances in medica

After an exciting time at the 10th Annual OHDSI Global Symposium at the Hyatt Regency in New Brunswick, NJ, SciForce is coming back with new energy! With over 470 experts gathered from around the world, our team, led by Polina Talapova, explored the latest tools and methods in OHDSI and OMOP. We tackled topics like data conversion, geospatial vocabularies, and Jackalope benchmarking, gaining valuable insights and sharing strategies to help move healthcare research forward. Educational Tutorial (

Predictive maintenance (PdM) is quickly becoming a must-have for industries looking to avoid the headaches of unexpected equipment failures. Imagine a manufacturing plant where a critical machine breaks down suddenly, halting production and costing thousands of dollars per hour in lost output. PdM helps prevent these costly surprises by predicting when equipment might fail, reducing downtime, and keeping operations running smoothly. As more businesses realize the benefits of catching problems be

Each nation has its ancient monument or a pagan holiday — the relic of the days when our ancestors tried to persuade their gods to give them more rain, no rain, better harvest, fewer wars and many other things considered essential for survival. However, neither Stonehenge nor jumping over fire could predict the gods’ reaction. It was a totally reactive world with no forecast. However, as time passed, people started to look into the future more inquisitively trying to understand what would be wai

Current advances in technology are in many ways fueled by the growing flow of data coming from multiple sources and analyzed to create competitive advantage. Both individual users and businesses are switching to a digital system¹, which in turn generates pools of information. In their turn, organizations share data with other companies, giving rise to digital ecosystems that begin to blur traditional industry borders. As the amount of data available grows, the size, diversity, and applications o

If we think of the most successful and widespread applications of machine learning in business, one of the examples would be recommender systems. Each time you visit Amazon or Netflix, you see recommended items or movies that you might like — the product of recommender systems incorporated by these companies. Though a recommender system is a rather simple algorithm that discovers patterns in a dataset, rates items and shows the user the items that they might rate highly, they have the power to b

It is quite often that in our blog we explore intricate connections between state-of-the-art technologies, or explore the mesmerizing depth of a new technique. However, AI or data science is not only bragging about new exciting methods that boost accuracy by 2% (which is a big gain) but about making data and technology work for you. It will help you increase sales, understand your customers, predict future faults in process lines, make an insightful presentation, submit a term project, or have a