Enlitic uses deep learning to make doctors faster and more accurate
Our Mission
Every time a doctor sees a patient, they are solving a complex data problem. The goal of each case is to arrive at an optimal treatment decision based on many forms of clinical information, such as the patient’s history, symptoms, lab tests, and medical images. The quality and quantity of this data is rapidly improving—it’s estimated to grow over 50-fold this decade, to 25,000 petabytes worldwide by 2020. Our world-class team of medical professionals and data scientists has made it our mission to improve patient outcomes by using this data to its maximum potential.
Enlitic uses deep learning to distill actionable insights from billions of clinical cases. We build solutions to help doctors leverage the collective intelligence of the medical community.
Deep Learning
Deep learning is a technology inspired by the workings of the human brain. Networks of artificial neurons analyze large datasets to automatically discover underlying patterns, without human intervention. Enlitic’s deep learning networks examine millions of images to automatically learn to identify disease.
Unlike traditional Computer Aided Diagnostics (CAD), deep learning networks can scout for many diseases at once. They can also provide rich insights in areas such as early detection, treatment planning, and disease monitoring.
Our Solutions
Enlitic works with a wide range of partners and data sources to develop state-of-the-art clinical decision support products.
Our deep learning technology can incorporate a wide range of unstructured medical data, including radiology and pathology images, laboratory results such as blood tests and EKGs, genomics, patient histories, and electronic health records (EHRs). This richness allows higher accuracy and deeper insights for every patient.
Our solutions integrate seamlessly into your existing health system infrastructure. For example, our radiology solutions communicate with third party image viewers and archiving systems.
PATIENT TRIAGE
Every year, over 300 million diagnostic radiology images are taken in the United States alone. As demand grows for diagnostic services, so does pressure on healthcare providers to operate more efficiently and accurately, at scale.
Our patient triaging solutions scan your incoming cases for multiple clinical findings, determine their priority, and route them to the most appropriate doctor in your network. Enlitic’s technology can interpret a medical image in milliseconds —up to 10,000 times faster than the average radiologist.
SCREENING PROGRAMS
Many populations that are at risk of developing a specific disease are recommended to be regularly checked, even when seemingly healthy. Nearly 70% of U.S. women over 40 receive biannual breast cancer tests. Other screening programs exist for prostate, cervical, and lung cancer.
Our screening solutions quickly analyze cases to discover and highlight suspicious findings, helping your doctors work efficiently when dealing with large patient loads. In benchmarking tests against the publicly available LIDC lung cancer screening dataset, Enlitic’s technology can judge the malignancy of nodules in chest CT images 50% more accurately than an expert panel of radiologists.
REAL-TIME CLINICAL SUPPORT
The National Institute of Medicine estimates that diagnostic errors affect 12 million Americans every year. More accurate and efficient decision support tools for doctors could greatly reduce that number.
Our real-time clinical support solutions provide workflow-integrated guidance to help your doctors interpret challenging cases. For example, Enlitic's deep learning technology can detect tiny fractures as small as 0.01% of an X-ray image. A heatmap overlay draws the radiologist’s attention to the findings.
RETROSPECTIVE ANALYSIS
Radiology suffers from high error rates; studies show that false positive rates can be up to 2%, while false negative rates can exceed 25%. Peer review and clinical quality assurance processes can improve accuracy, but are also time-consuming and costly.
Our retrospective analysis solutions rapidly evaluate large numbers of your past cases to reveal detailed insights into your network’s clinical performance. Retrospective analysis can also be a valuable tool outside the hospital, such as in clinical trials and drug development.
Enlitic is also developing products beyond the above categories. In addition to novel and targeted solutions in radiology, we are interested in pharmaceutical development, lab testing, and other data-rich opportunities in healthcare.
Partnership
We work with partners including healthcare providers, academic research institutions, and the pharmaceutical industry to develop our deep learning solutions. Please reach out if you’re interested in implementing Enlitic technology, contributing new data or clinical insights to our research, or working with us to develop new products.
Meet us at RSNA!
We will be demoing several of our solutions at RSNA 2016. Please visit us at booth North - Hall B: 8001 or email us at info@enlitic.com to schedule a meeting!
Enlitic uses deep learning to make doctors faster and more accurate
Upcoming Press Events
Want to meet the team or see some live demos? Join us for one of our upcoming events or presentations!
Our Mission
Every time a doctor sees a patient, they are solving a complex data problem. The goal of each case is to arrive at an optimal treatment decision based on many forms of clinical information, such as the patient’s history, symptoms, lab tests, and medical images. The quality and quantity of this data is rapidly improving—it’s estimated to grow over 50-fold this decade, to 25,000 petabytes worldwide by 2020. Our world-class team of medical professionals and data scientists has made it our mission to improve patient outcomes by using this data to its maximum potential.
Enlitic uses deep learning to distill actionable insights from billions of clinical cases. We build solutions to help doctors leverage the collective intelligence of the medical community.
Deep Learning
Deep learning is a technology inspired by the workings of the human brain. Networks of artificial neurons analyze large datasets to automatically discover underlying patterns, without human intervention. Enlitic’s deep learning networks examine millions of images to automatically learn to identify disease.
Unlike traditional Computer Aided Diagnostics (CAD), deep learning networks can scout for many diseases at once. They can also provide rich insights in areas such as early detection, treatment planning, and disease monitoring.
Our Solutions
Enlitic works with a wide range of partners and data sources to develop state-of-the-art clinical decision support products.
Our deep learning technology can incorporate a wide range of unstructured medical data, including radiology and pathology images, laboratory results such as blood tests and EKGs, genomics, patient histories, and electronic health records (EHRs). This richness allows higher accuracy and deeper insights for every patient.
Our solutions integrate seamlessly into your existing health system infrastructure. For example, our radiology solutions communicate with third party image viewers and archiving systems.
PATIENT TRIAGE
Every year, over 300 million diagnostic radiology images are taken in the United States alone. As demand grows for diagnostic services, so does pressure on healthcare providers to operate more efficiently and accurately, at scale.
Our patient triaging solutions scan your incoming cases for multiple clinical findings, determine their priority, and route them to the most appropriate doctor in your network. Enlitic’s technology can interpret a medical image in milliseconds —up to 10,000 times faster than the average radiologist.
SCREENING PROGRAMS
Many populations that are at risk of developing a specific disease are recommended to be regularly checked, even when seemingly healthy. Nearly 70% of U.S. women over 40 receive biannual breast cancer tests. Other screening programs exist for prostate, cervical, and lung cancer.
Our screening solutions quickly analyze cases to discover and highlight suspicious findings, helping your doctors work efficiently when dealing with large patient loads. In benchmarking tests against the publicly available LIDC lung cancer screening dataset, Enlitic’s technology can judge the malignancy of nodules in chest CT images 50% more accurately than an expert panel of radiologists.
REAL-TIME CLINICAL SUPPORT
The National Institute of Medicine estimates that diagnostic errors affect 12 million Americans every year. More accurate and efficient decision support tools for doctors could greatly reduce that number.
Our real-time clinical support solutions provide workflow-integrated guidance to help your doctors interpret challenging cases. For example, Enlitic's deep learning technology can detect tiny fractures as small as 0.01% of an X-ray image. A heatmap overlay draws the radiologist’s attention to the findings.
RETROSPECTIVE ANALYSIS
Radiology suffers from high error rates; studies show that false positive rates can be up to 2%, while false negative rates can exceed 25%. Peer review and clinical quality assurance processes can improve accuracy, but are also time-consuming and costly.
Our retrospective analysis solutions rapidly evaluate large numbers of your past cases to reveal detailed insights into your network’s clinical performance. Retrospective analysis can also be a valuable tool outside the hospital, such as in clinical trials and drug development.
Enlitic is also developing products beyond the above categories. In addition to novel and targeted solutions in radiology, we are interested in pharmaceutical development, lab testing, and other data-rich opportunities in healthcare.
Partnership
We work with partners including healthcare providers, academic research institutions, and the pharmaceutical industry to develop our deep learning solutions. Please reach out if you’re interested in implementing Enlitic technology, contributing new data or clinical insights to our research, or working with us to develop new products.