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...

From interpreting lab tests, simplifying in-vitro fertilization, and personalizing cancer care to monitoring surgical video in real-time or aiding in the diagnosis of pneumothorax, the creativity and ingenuity evident in the flourishing AI research community is both astounding and heartening. #artificialintelligence   #healthcare   #WMIF   #WorldMedicalinnovationforum   The central dogma of the Information Technology requirement in medicine is software that can efficiently ‘read •• mine •• understand’ medical data; such as patient diagnostic information/ health data, radiography images, clinical trial data, and drug combination therapy data etc. The health care system contains not only the simple text records but also complex data ranging from graphs from the diagnosis labs to images from the radiology instruments. What if we could use image and text analytics to produce a computerized radiologist assistant which could quickly filter to clinicians/radiologi...