Data Revolution in Healthcare and Lifesciences Industry

Image Credit: MIT Deep learning (also known as deep structured learning or hierarchical learning) is part of a broader family of machine learning methods based on artificial neural networks. MIT’s Computer Science and Artificial Intelligence Lab has developed a new deep learning-based AI prediction model that can anticipate the development of breast cancer up to five years in advance. Researchers working on the product also recognized that other similar projects have often had inherent bias because they were based overwhelmingly on white patient populations, and specifically designed their own model so that it is informed by “more equitable” data that ensures it’s “equally accurate for white and black women.” View this post on Instagram MobileODT creates smart colposcopy and visual assessment solutions for women's health clinicians at the point of care.EVA COLPO is a portable, Internet-connected, and FDA-cleared colposcope th...

Artificial intelligence’s #AI transformative power is reverberating across many industries, but in one healthcare its impact promises to be truly life-changing. The total public and private sector investment in healthcare AI are stunning: All told, it is expected to reach $6.6 billion by 2021, according to some estimates. Even more staggering, Accenture predicts that the top AI applications may result in annual savings of $150 billion by 2026. In theory, artificial intelligence and machine learning (AI/ML) can be applied to nearly every process in healthcare. In practice, however, entrepreneurs, enterprise leaders, and investors need to discriminate between incremental improvements and the 10X improvements that will transform the industry. In developing markets as well #AI driven companies are gaining attention and VC. Companies like Mfine has raised more than $24 million and has around 200 staff in Bengaluru and Hyderabad. But #AI faces several hurdles as well. When patient fi...