Here we dive deeper into how applied ML & AI resolve real challenges for Healthcare organizations
Face mask detection for Medical Imaging Center "Sanitas"
Sanitas enforces PPE compliance, ensures safety of their staff and patients amid COVID-19 pandemic. See how VITech Lab team resolved the challenge for constant PPE monitoring with the AI-powered software.
Improving Patient Flow: How to provide diagnostics accuracy while lacking time
In this article, we will delve into only one of the many facets of the US healthcare system that need reform — inefficient patient flow. We will explore how overworked medical personnel in the United States are, cover the consequences of the coronavirus pandemic in terms of diagnostics efficiency, and demonstrate how automation and AI can help doctors serve more patients while staying safe and protected.
How Machine Learning reduces costs spent on treatment and care
According to research made by Syft in 2018, hospitals spend over $25 billion more than necessary in their supply chains despite having the ability to save an average of 17.7% in their total supply expenses. Now artificial intelligence (AI) and machine learning (ML) can decrease costs spent for such stuff. But how?
Human Factors in Safety Control: Epidemiological Safety at Risk
In this article, we will explore why businesses automate safety control and why over-reliance on safety officers and manual routines can be dangerous to employees. We will talk about safety in healthcare organizations, including epidemiological safety.
Machine Learning in Healthcare: Fundamental Challenges vs. Immense Opportunities
Could AI and machine learning deliver healthcare advances while bringing down costs and improving affordability? We have reviewed the current state and scope of machine learning in healthcare, looked into the challenges organizations in healthcare face today and the benefits they expect to reap while implementing specific machine learning use cases.
VITech Lab Survey Insights: State of Data Science and ML in Healthcare
VITech Lab is pleased to reveal the results of the State of Data Science and ML in Healthcare survey that we conducted on LinkedIn in 2019. The survey sought to look into the scope and patterns of adoption of data science and machine learning in the healthcare industry.
How to achieve earlier lung disease detection: the automated approach
What challenges do doctors face while diagnosing lung diseases? How can we guarantee a precise accuracy, when a doctor has nearly 15 minutes on each patient? Lung disease identification and classification appears to a be task easily resolved by AI-powered solution. Read more to learn about computer-assisted pneumonia, COVID-19 and pneumotorax detection.
Machine Learning (ML) algorithms focused on medical image analysis have revolutionized the diagnosis process. Now doctors can detect more diseases than previously. For example, more genetic illnesses can be recognized, which were not diagnosed before. Let's look at use cases and illnesses AI can help with.
"Meet my assistant, an ML-based system" or why we use Computer-Aided Systems in Healthcare
How to shorten the time spent on diagnostics and release precious doctor's on patient care? How to speed-up diagnostics and increase accuracy? In this article, we will talk about computer-aided systems and look into specific AI-powered solutions that help physicians and administrative personnel drive efficiencies in healthcare.
New business reality: how to provide a safe working environment during and after the pandemic?
Covid 19 has been the hot topic for us all over the last few months, but now it looks like we are returning to something like the new reality. Nowadays not only healthcare workers rely on personal protective equipment to protect themselves and their patients from being infected and infecting others. People have to use PPE in such places and conditions as they could not even imagine before.