Excited to Display our Cutting Edge Machine Learning Capabilities at DIA 2018 Booth #2705by Shweta Mishra
Machine Learning applications have the potential to increase efficiency research and development in the healthcare sector. According to a report by McKinsey, big data and machine learning in pharma and medicine could generate a value of up to $100B annually, by contributing to better decision-making, improved enrolment in clinical trials, and creation of new tool for physicians and other stakeholders in the healthcare industry.
Machine Learning platforms for clinical trials data can help find ways to collect and use various kinds of health data more efficiently. Moreover, using Machine Learning to identify suitable candidates for clinical trials may allow to consider more factors while choosing candidates for a particular trial, making the target population more specific, reducing patient risk, hence, making the trials shorter and less expensive.
Forte Research Systems benchmark data suggests, “only 7 of 100 people interested in enrolling in a clinical trial complete the trial process from start to finish.”
Very soon, TrialX will be coming up with a new version of the product – iConnect 3.0 which will have improved user interface, added clinical trials search features, and features that will make it easier for researchers to keep track of their clinical trials.
iConnect powers all clinical trials search at CenterWatch, since November last year. CenterWatch has been a reliable source and global destination for clinical trials information since its inception in 1994, and clinical trials professionals as well as patients trust it to get any information related to clinical trials.
iConnect clinical trial management system is also currently being used by organizations like NYU, UPENN and BIDMC.
We will be happy to see you and share more between June 24-28, 2018 at booth #2705.
See you in Boston then!