What AI can do with unstructured data in healthcare

Improve data protection and minimize paperwork

Most security disasters in the healthcare industry are caused first by human error and misuse and physical theft and hacking second. Electronic Health Records or EHRs not only structure patient information but also allow for safe access and more personalized care.

Increase diagnostics accuracy

In the US alone, over 12 million patients are misdiagnosed annually. Deep learning applied to healthcare can radically improve that statistic: Instead of following a routine checklist, healthcare professionals can benefit from the informative by-product of algorithms that can read data using computer vision, text and sound recognition, and natural language processing.

Boost clinical performance

Running any medical facility is a complex, multi-faceted undertaking rife with the possibility of making unfortunate decisions. The obvious, well-documented risk level is high. Data-driven software provides clinicians with the opportunity to make better sense of their data – schedule more efficiently, create smarter reports with Business Intelligence, and automatically manage supplies. Making these decisions with far greater ease saves time and allows medical staff more time to concentrate on medicine.

Uncover AI opportunities in Healthcare

Medical image analysis using computer vision

Use computer vision on various radiology studies to identify tumors, patterns, and disease progression or regression.

Precision medicine using patient data analytics

Provide personalized healthcare by analyzing the full medical history through Electronic Health Records. Use the information you already have to create finely-focused treatment.

Simplified data management with Natural Language Processing

Incorporate speech recognition and NLP to record clinical documentation, make medical data more accessible to patients, and perform medical policy assessment.

Intelligent administrative workflow assistance

Transform how you do your healthcare business with ML for clinical data analysis and management. Eliminate routine tasks for medical staff and apply smart scheduling to save time for doctors and patients.

Faster and more accurate pharmaceutical research

Automate research efforts using machine learning algorithms. Save months or even years of research and deliver a cure faster by feeding AI billions of already available data points.

Medical fraud and data security solutions

Apply predictive analytics and deep learning techniques to predict fraud, detect suspicious behavior in real time, prevent patient data breach, and avoid upcoding.

Patient monitoring using wearables

Collect and make use of data generated by human bodies. Track chronic diseases, incorporate medical recommendations into patient lifestyles, and predict disorders.