We now find ourselves on Day 2 of the TEDMED experience, where Session 2 delves into the concept of “How Can Big Data Become Real Wisdom?”. In the first part of the day, speakers addressed the issue of how information flow, although constant, can often be meaningless unless it’s properly orchestrated.

Among this Session speakers were Deborah Estrin, co-founder of Open mHealth, an organization that seeks to build an open software architecture in mHealth to enable more interconnected and effective mHealth ecosystem. She shared her insights on how even small data could be used by mobile carriers and physicians to create a package of pertinent information for our individual needs. According to Open mHealth,

Through a shared set of open APIs, both open and proprietary software modules, applications and data can be ‘mixed and matched’, and more meaningful insights derived through reusable data processing and visualization modules. Visualization modules can pull in, smooth and combine data streams from a range of sensors and application sources to reveal correlative insights into patients’ health, or evaluation modules could be embedded directly into an app to allow real-time assessment of a treatment — such as how a patient responds to one treatment compared to another, and even prove the clinical impact of the app itself. Enhanced integration at both module and application levels allows products to be more nimbly adapted and customized to maximize potential impact.

Elizabeth Marincola, president of the nonprofit membership organization Society for Science & the Public (SSP), spoke about protected scientific knowledge and its drawbacks, she posed the question on whether or not this is still necessary. Among SSP’s range of endeavors are the promotion of discovery and innovation through programs like the Science Talent Search, sponsored by Intel but administered by SSP.

As we explored the Hive, a demo and exhibition area, a little stand for a company called CrowdMed jumped out at us. This company proposes something quite controversial but interesting – crowdsourcing medical diagnostics. Patients submit their clinical chart as well as all the tests and studies that have been done so far and users called “medical detectives” or “MDs” vote on the diagnostic that they feel fits best. There’s a gamified aspect included in the voting system as well in which the “MDs” rank the level of confidence they have on their “guess”.  So far their pool sample is quite small but they are confident that this can help physicians solve trickier cases.