Enlitic是一家来自美国加州旧金山的科技公司，连续两年蝉联MIT Technology Review杂志评选的全球人工智能公司第35（2015）和第14名（2016）。该公司致力于运用人工智能及机器学习等前沿技术来辅助医疗诊断。公司采用时下最先进的深度学习算法对医学图像、诊断书、临床试验等大量医疗数据进行挖掘，实现了快速、准确、可行的健康诊断。
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 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.
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.