Agenda

Predictive Analytics World for Healthcare Las Vegas 2020

May 31-June 4, 2020 – Caesars Palace, Las Vegas


Click here to view the full 8-track agenda for the five co-located conferences at Machine Learning Week (PAW Business, PAW Financial, PAW Healthcare, PAW Industry 4.0, and Deep Learning World).

Pre-Conference Workshops - Sunday, May 31st, 2020

8:30 am
Pre-Conference Training Workshop

Full-day: 8:30am – 4:30pm

This one day workshop reviews major big data success stories that have transformed businesses and created new markets. Click workshop title above for the fully detailed description. 

Session description
Instructor
Marc Smith
Chief Social Scientist
Connected Action Consulting Group
Pre-Conference Training Workshop

Full-day: 8:30am – 4:30pm

Gain experience driving R for predictive modeling across real examples and data sets. Survey the pertinent modeling packages.  Click workshop title above for the fully detailed description. 

Session description
Instructor
Robert MuenchenUniversity of Tennessee
Manager of Research Computing Support
University of Tennessee
4:30 pm
End of Sunday Pre-Conference Training Workshops
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Pre-Conference Workshops - Monday, June 1st, 2020

8:30 am
Pre-Conference Training Workshop

Full-day: 8:30am – 4:30pm

This one-day session surveys standard and advanced methods for predictive modeling (aka machine learning). Click workshop title above for the fully detailed description. 

Session description
Instructor
John Elder Ph.D.Elder Research
Founder & Chair
Elder Research
Pre-Conference Training Workshop

Full-day: 8:30am – 4:30pm

This one-day introductory workshop dives deep. You will explore deep neural classification, LSTM time series analysis, convolutional image classification, advanced data clustering, bandit algorithms, and reinforcement learning. Click workshop title above for the fully detailed description. 

Session description
Instructor
James McCaffreyMicrosoft
Senior Scientist Engineer
Microsoft
Pre-Conference Training Workshop

Full-day: 8:30am – 4:30pm

Python leads as a top machine learning solution – thanks largely to its extensive battery of powerful open source machine learning libraries. It’s also one of the most important, powerful programming languages in general. Click workshop title above for the fully detailed description. 

Session description
Instructor
Clinton BrownleyWhatsApp
Data Scientist
WhatsApp
Pre-Conference Training Workshop

Full-day: 8:30am – 4:30pm

Machine learning improves operations only when its predictive models are deployed, integrated and acted upon – that is, only when you operationalize it.  Click workshop title above for the fully detailed description. 

Session description
Instructor
James TaylorDecision Management Solutions
CEO
Decision Management Solutions
4:30 pm
End of Monday Pre-Conference Training Workshops
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Predictive Analytics World for Healthcare - Las Vegas - Day 1 - Tuesday, June 2nd, 2020

8:00 am
Registration & Networking Breakfast
8:45 am
Eric SiegelPredictive Analytics World
Conference Founder
Predictive Analytics World
8:50 am
MACHINE LEARNING WEEK KEYNOTE
Lessons from: Lyft

In this keynote address, Gil Arditi will cover the areas of machine learning development at Lyft, talk about friction points in the model lifecycle – from prototyping and feature engineering to production deployment – and show how Lyft streamlined this process internally. He will also cover a step-by-step example of a model that was recently developed and taken to production.

Session description
Speaker
Gil ArditiLyft
Product Lead, Machine Learning
Lyft
9:15 am
MACHINE LEARNING WEEK KEYNOTE
Lessons from: Google

As principles purporting to guide the ethical development of Artificial Intelligence proliferate, there are questions on what they actually mean in practice. How are they interpreted? How are they applied? How can engineers and product managers be expected to grapple with questions that have puzzled philosophers since the dawn of civilization, like how to create more equitable and fair outcomes for everyone, and how to understand the impact on society of tools and technologies that haven't even been created yet. To help us understand how Google is wrestling with these questions and more, Jen Gennai, Head of Responsible Innovation at Google, will run through past, present and future learnings and challenges related to the creation and adoption of Google's AI Principles.

Session description
Speaker
Jen GennaiGoogle
Head of Responsible Innovation, Global Affairs
Google
9:40 am
The Session Description will be available shortly.
Session description
10:00 am
Exhibits & Morning Coffee Break
10:30 am
Case Study: Cedars-Sinai Medical Center

Improving hospital-wide patient flow requires an appreciation of the hospital as an interconnected, interdependent system of care. Learn how supervised machine learning was used to create predictive models for length of stay, emergency department (ED) arrival, ED admissions, aggregate discharges, and total bed census to reduce patient wait times, reduce staff overtime, improve patient outcomes, and improve patient and clinician satisfaction.

Session description
Speaker
Michael ThompsonCedars-Sinai Medical Center
Executive Director, Enterprise Data Intelligence
Cedars-Sinai Medical Center
11:15 am
5-minute transition between sessions
11:20 am
Case Study: Mayo Clinic

Clinical utilization of advanced predictive analytics faces many typically mentioned barriers, specifically: lack of interpretability, lack of uncertainty measures, and inability to handle disparate groups which hinders generalizability. Herein, we provide a framework utilizing artificial neural network analysis to predict changes in patient reported outcomes, which provide solutions to these common issues utilizing local interpretable model-agnostic explanations (LIME), repeated network simulation, and propensity score analysis. In particular, we aim to analyze the association between treatment modality and patient reported adverse events reported assessed by the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAETM).

Session description
Speakers
Todd DeweesMayo Clinic
Associate Professor of Biostatistics, Radiation Oncology
Mayo Clinic
Michael GolafsharMayo Clinic
Statistical Programmer Analyst
Mayo Clinic
12:05 pm
Lunch
1:30 pm
KEYNOTE

Physicians should be lining up, reaching over each other to get their hands on the AI that can help them deliver better care, right? This same line was said about the promise of the EHR, and today only 40.3% of physicians agree that their EHRs alerts prevent mistakes (source: KLAS Arch Collaborative, n = 10,938). Why are these technologies not taking hold? Join Taylor Davis, KLAS Research’s VP of Research, as he shares findings from the KLAS Arch Collaborative and the KLAS 2019 AI Study. Learn how we can better develop these technologies with physicians, delivering them for physicians (instead of to physicians).

Session description
Speaker
Taylor DavisKLAS
VP of Research
KLAS
2:15 pm
The Session Description will be available shortly.
Session description
2:35 pm
5-minute transition between sessions
2:40 pm
Reinventing Primary Care Medicine

Join Vickie Rice, VP of Innovative Strategies for CareATC, for a look at their Primary Care practice model that is turning today’s sick-care medical system upside down with the aid of an Artificial Intelligence program that not only uses predictive analytics to identify risk in their supported populations but also provides prescriptive analytics that focuses their providers on proactive interventions to prevent adverse events such as emergency room utilization and inpatient hospital admissions.

Session description
Speaker
Vickie RiceCareATC, Inc.
Vice President of Innovative Strategies
CareATC, Inc.
3:25 pm
Exhibits & Afternoon Break
3:55 pm
Case Study: Eli Lilly and Company

Non-alcoholic fatty liver disease (NAFLD) is the leading cause of chronic liver disease worldwide and affecting 25% of the global adult population. NAFLD may progress to non-alcoholic steatohepatitis (NASH) and thus predisposes to liver cirrhosis, end stage liver disease and hepatocellular carcinoma (HCC). In the United States, NASH is expected to become the leading cause of liver transplantation by 2020. Thus, the development of blood biomarkers suitable for prognostication, selection of patients for treatment and monitoring is an unmet clinical need. We will demonstrate how machine learning has the ability to model and predict disease progression using protein biomarker data.

Session description
Speaker
Yu ChenEli Lilly & Company
Research Advisor
Eli Lilly & Company
4:40 pm
5-minute transition between sessions
4:45 pm
Case Study: Blood Supply Management and Forecasting

Blood, platelets and other transferable fluids are critical for patient health –particularly during trauma treatment, surgery and chemotherapy. Every day OneBlood collects, processes and delivers thousands of units of blood and blood products; keeping hospitals throughout the Southeastern US ready to provide life-saving healthcare. OneBlood is using predictive modeling to better understand and to shape donor behavior. Additionally, by forecasting hospital blood product needs, OneBlood is able to anticipate demand and modify donor recruitment and the processing of blood products. This ensures that hospitals have the right blood products in the right amounts at the right time.

Session description
Speakers
Kelley CountsOneBlood
Data Scientist
OneBlood
Karl RexerRexer Analytics
President
Rexer Analytics
5:30 pm
Networking Reception
7:00 pm
End of first Conference Day

Predictive Analytics World for Healthcare - Las Vegas - Day 2 - Wednesday, June 3rd, 2020

8:00 am
Registration & Networking Breakfast
8:45 am
8:55 am
KEYNOTE
The Session Description will be available shortly.
Session description
Speaker
John Elder Ph.D.Elder Research
Founder & Chair
Elder Research
9:40 am
The Session Description will be available shortly.
Session description
10:00 am
5-minute transition between sessions
10:05 am
Case Study: NorthShore University Health System

In-hospital and out-of-hospital mortality and readmission prediction models have been extensively covered in literature intended for scientists and practitioners. Adaptive development that feeds real-time performance data back into model calibration has received much less attention. This presentation shows how operational decisions influence the structure of the developed framework and how models are affected by implementation decisions. Aligning the operational and predictive analytics functions helps create a unified scalable multi-purpose prescriptive analytics framework within the organization. The data science function can help solve the operational challenges arising from such implementation by using additional analysis obtained through continuous monitoring of live data.

Session description
Speaker
Daniel Chertok PhDNorthShore University HealthSystem
Sr. Data Scientist
NorthShore University HealthSystem
10:50 am
Exhibits & Morning Coffee Break
11:20 am
Cancer Prediction
The Session Description will be available shortly.
Session description
Speaker
Bob NisbetUniversity of California, Irvine Extension
Instructor
University of California, Irvine
12:05 pm
Lunch
1:15 pm
The Session Description will be available shortly.
Session description
2:00 pm
The Session Description will be available shortly.
Session description
2:10 pm
5-minute transition between sessions
2:15 pm
Case Study: West African Ebola Outbreak

This talk overviews Quantopo's efforts to understand the anatomy of an Ebola outbreak and predict how an outbreak will change under different responses. This work extends previous work on the 2014 West African Ebola outbreak and operational support in Mali. Results presented in this talk were used to support disaster response ground operations in the Democratic Republic of the Congo and position workers in areas likely to be hit the hardest in the weeks after the analysis. Regrettably, operational support was stymied by violence against aid workers and lack of international funding for a swift response.

Session description
Speaker
Colleen Farrelly
Co-Founder & Chief Scientist
Quantopo LLC
3:00 pm
Exhibits & Afternoon Break
3:30 pm
3:30pm - 3:50pm
Addressing Bias

Algorithms are used in many high-stakes decisions that affect our daily lives. As we develop AI systems that automate decisions in healthcare, how do we ensure trust and fairness? In this talk, we will discuss how to address algorithmic bias in building trusted AI systems. We will start with an introduction of various components of trust: fairness, accountability, transparency, and ethics. We will discuss various case studies to illustrate how fairness sneaks into algorithms. We will then focus on the tools & techniques that practitioners can use to detect, mitigate and monitor bias in AI applications.

Session description
Speaker
Zeydy Ortiz
CEO
DataCrunch Lab
3:55pm - 4:15pm
Child Behavioral Healthcare

The transformative power of artificial intelligence has taken the world by storm, and healthcare is no exception. In this talk we explore the potential of AI to streamline, scale, and improve the diagnostics and digital therapeutics of behavioral disorders for young children such as autism, ADHD, and speech & language disorders. We showcase several digital diagnostic and therapeutic products and their underlying algorithms, and take the audience through Cognoa's journey to develop and validate them.

Session description
Speaker
Halim AbbasCognoa
Vice President of Data Science
Cognoa
4:15 pm
5-minute transition between sessions
4:20 pm
Case Study: Capital District Physicians’ Health Plan

Given the vast amount of unstructured data available to health care payers in various forms –ranging from clinical records to audio recordings –the need to build out and apply a natural language processing (NLP) platform is essential. This session will discuss the foundational strategy and components being developed at CDPHP, a mid-size health care payer in New York’s Capital Region. Real-world use cases will be discussed, focusing on increasing efficiency and accuracy, all while reducing error. There will also be discussion of applications focused on member insights and experience. Practical examples will be taken from HEDIS reporting, risk revenue, and member engagement.

Session description
Speaker
Matthew PietrzykowskiCapital District Physicians’ Health Plan
Principal Data Scientist
Capital District Physicians' Health Plan
5:05 pm
End of second Conference Day
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Post-Conference Workshops - Thursday, June 4th, 2020

8:30 am
Post-Conference Training Workshop

Full-day: 8:30am – 4:30pm

This one-day session reveals the subtle mistakes analytics practitioners often make when facing a new challenge (the “deadly dozen”), and clearly explains the advanced methods seasoned experts use to avoid those pitfalls and build accurate and reliable models.  Click workshop title above for the fully detailed description.

Session description
Instructor
John Elder Ph.D.Elder Research
Founder & Chair
Elder Research
Post-Conference Training Workshop

Full-day: 8:30am – 4:30pm

Gain the power to extract signals from big data on your own, without relying on data engineers and Hadoop specialists. Click workshop title above for the fully detailed description.

Session description
Instructor
James Casaletto
PhD Candidate
UC Santa Cruz Genomics Institute and former Senior Solutions Architect, MapR
Post-Conference Training Workshop

Full-day: 8:30am – 4:30pm

This workshop dives into the key ensemble approaches, including Bagging, Random Forests, and Stochastic Gradient Boosting. Click workshop title above for the fully detailed description.

Session description
Instructor
Dean AbbottSmarterHQ
Co-Founder and Chief Data Scientist
SmarterHQ
Post-Conference Training Workshop

Full-day: 8:30am – 4:30pm

During this workshop, you will gain hands-on experience deploying deep learning on Google’s TPUs (Tensor Processing Units) at this one-day workshop, scheduled the day immediately after the Deep Learning World and Predictive Analytics World two-day conferences.  Click workshop title above for the fully detailed description.

Session description
4:30 pm
End of Post-Conference Training Workshops
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