10 Fastest Growing Healthcare Companies 2019
The Silicon Review
Paige is a firm that is completely focused on transforming the diagnosis and treatment of cancer. Through cutting edge AI, it helps pathologists improve the efficacy and efficiency of their work, researchers generate new insights, and clinicians improve patient care. Paige’s Aspiration is to build the Best AI in Clinical Medicine
The Firm’s Strategy
Paige’s short term plan is to deliver a series of AI disease modules that allow pathologists to improve the scalability of their work, enabling them to provide better care, at a lower cost. The medium to long-term plan is to develop new treatment paradigms that integrate computational pathology with electronic health records, genomic and other clinical data. Paige fosters national and global partnerships with academic medical centres, clinical labs, and pharmaceutical companies to enhance the field of computational pathology and change how cancer is diagnosed and treated.
The Abbreviation of PAIGE
Pathology
Pathology is the cornerstone of a cancer diagnosis. The field is on the cusp of a revolution from a qualitative to a quantitative discipline. PAIGE's algorithm is trained with diagnoses from the world's foremost cancer experts and hundreds of thousands of digital slides.
Artificial Intelligence
Artificial Intelligence is at PAIGE's core. Its experts have a decade of experience in building large scale machine learning systems for computational pathology. Now they are working on developing novel deep learning and ensemble models to create the first ever clinical-grade AI for pathology.
Guidance
PAIGE will guide pathologists, clinicians and researchers via its robust clinical decision support system. Clinical experts will gain massive efficiencies and reproducibility of their data.
Engine
Paige is the first to have AIRI, the most advanced architecture ever built for scale-out AI. AIRI has GPU performance of more than 10 petaFLOPS, allowing it to train the models at an unprecedented scale. The frim’s unique, scanner-neutral slide viewer will provide its end users with easy access to PAIGE.
At the heart of PAIGE are large-scale machine learning algorithms that are trained at petabyte-scale from tens of thousands of digital slides. Paige is developing novel deep learning algorithms based on convolutional and recurrent neural networks as well as generative models that are able to learn efficiently from an unprecedented wealth of visual and clinical data.
Medical AI at an unprecedented scale
PAIGE has a comprehensive license with MSK and exclusive rights to their library of 25 million pathology slides — one of the largest tumour pathology archives. PAIGE plans to build on to MSK's efforts and digitize millions of archived slides. This digital treasure, along with anonymized clinical data, allows the company to train models at scale.
Clinical Expertise
The firm’s data is enriched by an unmatched repository of annotated pathology slides, diagnosed by the world’s leading pathologists.
Investing for growth and leadership
As investors pour millions of dollars into startups applying artificial intelligence to medicine, pathology is at the forefront of what can be achieved. The company is backed by $25 million series financing.
The Leader of the Firm
Leo Grady, PhD | CEO
Seasoned healthcare technology leader with 15+ years of experience in prototyping, developing and bringing to the market advanced machine learning, computer vision and medical imaging technologies and products. Former SVP of Engineering for HeartFlow, where he led full stack technology and product development efforts in a variety of leadership roles at Siemens. Author of two published books, over 100 peer-reviewed journal and conference papers, and has over 300 issued or pending patents worldwide. He was inducted as a fellow in the American Institute for Medical and Biological Engineering in 2014, 2012 recipient of the Edison Patent Award in medical imaging. He has obtained B.sc degree from Electrical Engineering at the University of Vermont and PhD in Cognitive and Neural Systems from Boston University.