Bio IT World 2019 - Data Visualizations & Exploration Tools - Christine Lan, Lucidworks
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Presentation from Bio IT World, Boston | April 16-18, 2019 Track: Data Visualizations & Exploration Tools: Leveraging Machine Learning for Visualization Session Title: Simplifying the Adoption of Machine Learning for Real Time Clinical Data Insight and Decision Making Speaker: Christine Lan, Lucidworks
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Bio IT World 2019 - Data Visualizations & Exploration Tools - Christine Lan, Lucidworks
- 1. Simplifying the Adoption of Machine Learning for Real Time Clinical Data Insight and Decision Making Christine Lan
- 8. Data Sources Data Transformation Data Visualization Natural Language Processing > Synonym Generation Crowd-Sourced Relevancy > Personalized Recommendations Security > Role and Record Level Access Controls Scalability > No cubes and aggregations needed > 4B+ individual records User Workflow Oriented
- 9. Data Sources Data Transformation Data Visualization Natural Language Processing Crowd-Sourced Relevancy Security Scalability User-Centric Structured Manual BI Tools ALL your Data Smart and Automated Secure and User-Centric
- 10. Structured Manual BI Tools ALL your Data Smart and Automated Secure and User-Centric
- 12. Lucidworks Fusion + Pharma Shortened Product Launch Cycle. Connect patients to appropriate clinical trials through NLP and personalized ranked best matches using more sources like social media More Efficient R&D. Break down data silos across multiple functional areas by surfacing personalized content, experts, and conversations through smarter enterprise search and knowledge management Gathering Competitive Intelligence. Monitor the web (including social media like Twitter) to see what influential people are saying, keep track of patents through sources like Cortellis Competitive, determine how biosimilars are being positioned, and aggregate trends
- 13. Lucidworks Fusion + Pharma Shifting Global Regulatory Landscape. Surface relevant regulatory information, e.g. Cortellis Regulatory Intelligence and FDA sites both in US and abroad Compliance. Improve site search so patients can more easily find programs they’re eligible for to decrease medical non-compliance. Better create and monitor analytics in near real-time from trip reports and PAEs Site Search Analysis for Marketing. See what people are searching and clicking on your website so targeted marketing collateral can be created
- 15. Signals can include Industry-Leading Relevance with Signals Fusion captures, stores, and aggregates signals from a variety of sources to drive automated relevancy tuning to deliver best-in- class relevance. Clicks and Queries Geo-location User Behavior and Preferences User Search History Device
- 16. App Maturity Complexity Stage 3 Machine Learning Deliver the "next best action" to the user. Understand intention with query classification and intent, clustering, recommendations, and conversational search. Stage 2 Dynamic Application of Signals, Automated Relevancy, OpenNLP, Gazetteer Stage 1 Curated Rules, Signal Capture, Analytics, Security Stage 0 Basic Field Boosting, Synonyms, Phrase Matching Relevancy Strategy
Notes de l'éditeur
- Roche is for “value-based pricing” vs. voluntary price restraints R&D lifecycle through … FDA, compliance ect. Pricing transparency? Personalized medication for increased drug efficacy? Patients are identified to enroll in clinical trials based on more sources—for example, social media—than doctors’ visits. Furthermore, the criteria for including patients in a trial could take significantly more factors (for instance, genetic information) into account to target specific populations, thereby enabling trials that are smaller, shorter, less expensive, and more powerful. Trials are monitored in real time to rapidly identify safety or operational signals requiring action to avoid significant and potentially costly issues such as adverse events2 and unnecessary delays. Instead of rigid data silos that are difficult to exploit, data are captured electronically and flow easily between functions, for example, discovery and clinical development, as well as to external partners, for instance, physicians and contract research organizations (CROs). This easy flow is essential for powering the real-time and predictive analytics that generate business value. Site Search, help reduce medical non-compliance by making it easier for patients to find programs they’re eligible for
- Roche is for “value-based pricing” vs. voluntary price restraints R&D lifecycle through … FDA, compliance ect. Pricing transparency? Personalized medication for increased drug efficacy? Patients are identified to enroll in clinical trials based on more sources—for example, social media—than doctors’ visits. Furthermore, the criteria for including patients in a trial could take significantly more factors (for instance, genetic information) into account to target specific populations, thereby enabling trials that are smaller, shorter, less expensive, and more powerful. Trials are monitored in real time to rapidly identify safety or operational signals requiring action to avoid significant and potentially costly issues such as adverse events2 and unnecessary delays. Instead of rigid data silos that are difficult to exploit, data are captured electronically and flow easily between functions, for example, discovery and clinical development, as well as to external partners, for instance, physicians and contract research organizations (CROs). This easy flow is essential for powering the real-time and predictive analytics that generate business value. Site Search, help reduce medical non-compliance by making it easier for patients to find programs they’re eligible for
- Connectors are tricky to build from scratch…usually it takes somewhere between 1-3 months to build a connector…but luckily for you, we have over 30 OOB We have a ServiceNow connector OOB which customer like AllState Insurance are leveraging. We also have Slack and Box connectors OOB. I know you mentioned OneDrive during our last meeting and we will have that connector in our next release in July.
- Returning the most relevant result for a search query is at the heart of providing a great search experience for your users Lucidworks View UI is continuously keeping track of the key words users are typing in, the result set being returned and the specific search result users are clicking on or (not). This information is available to Fusion adminstrators through the Search Analytics dashboard Fusion is continuously capturing this data and aggregating it to automatically tune relevance and provide the most clicked on information for a particular search term on top of the search results. For example, if a user types in Holiday Schedule and 2017 Holiday schedule is the most clicked search result by previous users, then the 2017 Holiday Schedule will be boosted to the top of the result set. The location of the user is similarly used to boost local results over other locations. This is a fully automated process that is running on Apache Spark and managed by Fusion User Search History, Preferences and Device used to access search can similarly be used as inputs to automatically provide the most relevant result on top Apache Solr provides good search relevance out of the box, but needs to be continuously monitored and tuned as the underlying data being searched grows and changes With the Signals capability Fusion takes this even further and dynamically adjusts relevance that is tuned automatically to the way your users are searching Machine Learning models can be applied with Fusion to make signals based relevance even more powerful for even more smarter and relevant search Relevance with Fusion Signals is the best in the industry