Abstract Artificial intelligence (AI) is poised to broadly reshape medicine, potentially improving the experiences of both clinicians and patients …

Artificial intelligence (AI) is poised to broadly reshape medicine, … collection and safeguarding against the reinforcement of inequities (Fig.

For life science companies, healthcare providers, patients, and consumers, AI offers great potential to streamline processes and achieve better treatment results. Dr. Anna Bauer-Mehren describes the role of real-world data, data science or data analysis in pharmaceutical research and the resulting new opportunities for personalized medicine. In particular, she addresses the importance of high-quality data and Roche's efforts to make data FAIR. In their view, this is essential for the success of AI methods in R&D. Using several examples, she shows in which areas of pharmaceutical research AI is already being used successfully, but also discusses which areas still have great challenges.

In anticipation of his upcoming conference presentation at Predictive Analytics World for Business Las Vegas, May 31-June 4, 2020, we asked Kumaran Ponnambalam, Analytics Architect at Cisco, a few questions about their deployment of predictive analytics. Catch a glimpse of his presentation, Using Association Rules Mining for Segmentation and Profiling, and see what's in store at the PAW Business conference in Las Vegas. Q: In your work with predictive analytics, what behavior or outcome do your models predict? A: My models deal with natural language understanding for contact center voice calls. They transcribe the calls and derive call summaries, intent and sentiment based on the transcriptions.

For life science companies, healthcare providers, patients and consumers, AI offers great potential to streamline processes and achieve better treatment results. On the one hand, the findings from data generated in the real world setting could take personalized medicine to a new level by individually tailoring diagnosis and treatment in terms of effectiveness and safety to the patient. On the other hand, the linking of clinical study data and real world data with the enormous advances in biology and medicine is a prerequisite for more targeted research and more efficient development processes. In her talk Dr. Anna Bauer-Mehren describes the role of real world data, data science or data analysis in pharmaceutical research and the resulting new opportunities for personalized medicine. In particular, she addresses the importance of high quality data and Roche's efforts to make data FAIR.

Predictive Analytics World for Industry 4.0, the leading vendor-independent conference for applied predictive analytics is back, in Munich, 12-13 Jun. Discover and discuss the latest trends and technologies in machine & deep learning for the era of Internet of Things and artificial intelligence.

This one-day session surveys standard and advanced methods for predictive modeling (aka machine learning).

A dataset with M items has 2M subsets anyone of which may be the one satisfying our objective. With a good data display and interactivity our fantastic pattern-recognition defeats this combinatorial explosion by extracting insights from the visual patterns. This is the core reason for data visualization. With parallel coordinates the search for relations in multivariate data is transformed into a 2-D pattern recognition problem. Together with criteria for good query design, we illustrate this on several real datasets (financial, process control, credit-score, one with hundreds of variables) with stunning results.

Here are upcoming meetings and conferences, for July 2016 and beyond. Save 10% with the KDNUGGETS registration code. Aug 29 - Sep 1, Image Processing, Computer Vision and Machine Learning based on Optimization and PDE. Use code CDOINSUR to save 10% on registration. Sep 23, MLconf Atlanta Machine Learning Conference - mention "KDNuggets" and save 18%.

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