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...

Has your child suffered from an eye problem lately? It can be #glaucoma ! Many of the devices currently available for IOP measurement require cooperation from the subject so that accurate and repeatable reading can be obtained. Dr. Sirisha Senthil, MS, FRCS heading the VST Centre for Glaucoma care at LV Prasad Eye Institute mentioned that younger children who cannot cooperate for Goldmann applanation tonometer are tested with Icare tonometer in their Hospital. #ophthalmology #digitalhealth #eyes #child #medical #medical #innovation #diagnostics #LVPEI https://www.linkedin.com/pulse/glaucoma-detection-paediatric-setting-dr-ruchi-dass/?published=t For a vast majority of the population glaucoma in children is unheard of. It is a gradual process, and since there is almost no indication of loss of vision, many people do not realize they have it. Timely diagnosis of Glaucoma is hence, a challenge. When it comes to children, the challenge is even more significant. Children often cann...

Cell and gene therapies are becoming more and more popular because of encouraging clinical results worldwide. Major pharma manufacturing companies have invested in the concept's commercialization worldwide. Recently, we read about Takeda’s license for commercialization of Aloficel (developed by TiGenix), Celgene’s acquisition of Juno Therapeutics or Gilead’s acquisition of Kite Pharma. As this sector grows further, there is hope that more and more complex therapies will enter the market leading to a consequent increase in the number of treated patient population. This will put further pressure on manufacturing and R&D leading to larger adoption of QbD (Quality by design) principles. The data volume will increase significantly and that is where the concept of big data analytics will kick in. Data is important- it guides the manufacturing operations; allows proper monitoring and control to ensure quality and assures efficiency, production quality, and regulatory complian...