AI Summit Meeting Agenda

August 09, 2024

Friday November 8, 2024

The Impact of AI in Transforming Care in Cardiometabolic Disease

Evan D. Muse, MD, PhD, FACC, FAHA
Associate Clinical Professor and Associate Program Director  
MCTI Scripps Research Translational Institute  

Dr. Evan Muse is a preventive cardiologist dedicated to reducing the health burdens associated with heart disease. His mission is to identify risk factors in patients to optimize lifestyle and treatment strategies before the symptoms of heart disease manifest. He is an Associate Clinical Professor of Medicine and Associate Program Director for Research of the Cardiovascular Disease Fellowship at the Scripps Clinic, as well as an Assistant Professor of Molecular Medicine at the Scripps Research Translational Institute in La Jolla, California. 

As a physician-scientist, Dr. Muse aims to improve patient outcomes through the use of polygenic risk scores and digital medicine approaches, integrating genetics, lifestyle, and health data to optimize medical treatments and lifestyle recommendations. With a passion for cross-disciplinary collaboration, he has served as a judge for the Qualcomm Tricorder XPRIZE and IBM Watson AI XPRIZE competitions, sits on the Founding Members Council of the Digital Medicine Society, and is an Associate Editor for the Nature Partner Journal - Digital Medicine. 

Endocrinology and Hypertension

Maria-Christina Zennaro, MD, PhD 
Inserm, Université Paris Cité, Paris Cardiovascular Research Center-PARCC 

Maria-Christina Zennaro, MD, PhD, is Research Professor at the French National Institute of Health and Medical Research (Inserm), head of the team “Genetic mechanisms of aldosterone related disorders - towards integrative precision medicine” at the Paris Cardiovascular Research Center, Inserm and Université Paris Cité, and associated investigator at the Genetics Department of the European Hospital Georges Pompidou (HEGP) in Paris, France. Her research team has developed an integrated strategy to explore the genetics and genomics of aldosterone related disorders, in order to generate knowledge translatable to patient’s care. Maria-Christina Zennaro is coordinator of different EU-funded Horizon projects aiming at developing omics-based approaches for improved diagnosis and treatment efficacy inhypertension by biomarker-guided personalized decision support (www.ht-advance.eu). She is also partner of the Horizon 2020 MINDSHIFT project “Mechanistic Integration of vascular aND endocrine pathways for Subtyping Hypertension: an Innovative network approach for Future generation research Training”. She has served as European Society of Endocrinology - ESE Focus Area lead for Adrenal and Cardiovascular Endocrinology and was member of the annual meeting steering committee of the Endocrine Society. She is currently Deputy Treasurer of the French Society of Endocrinology, member of the executive committee of the European Council for Cardiovascular Research ECCR, member of the FIRENDO and ORKID networks for rare adrenal and kidney diseases, and member of the European Society of Hypertension - ESH Centre of Excellence for Hypertension at the HEGP. Her research has been awarded different prizes, including the « European Medal » of the Society for Endocrinology/British Endocrine Society in 2018.

Ambient and Wearable Devices, Biomedical Signal Processing, and Health Monitoring  

Edward Sazonov, PhD  
University of Alabama, Computer Laboratory of Ambient and Wearable Systems

Edward Sazonov (IEEE M’02, SM’11) received the Diploma of Systems Engineer from Khabarovsk State University of Technology, Russia, in 1993 and the PhD degree in Computer Engineering from West Virginia University, Morgantown, WV, in 2002. Currently he is a James R. Cudworth endowed Professor in the Department of Electrical and Computer Engineering at the University of Alabama, Tuscaloosa, AL and the head of the Computer Laboratory of Ambient and Wearable Systems. His research interests span wearable devices, sensor-based behavioral informatics and methods of biomedical signal processing and pattern recognition. Devices developed in his laboratory include a wearable sensor for objective detection and characterization of food intake (AIM – Automatic Ingestion Monitor); a highly accurate physical activity and gait monitor integrated into a shoe insole (SmartStep, winner of Bluetooth Innovation World Cup 2009); a wearable sensor system for monitoring of cigarette smoking (PACT); and others. The research in his lab was recognized by several awards, including best paper awards, President’s research award at the University of Alabama and others. In 2020 Dr. Sazonov served as a Fulbright Distinguished Chair at the University of Newcastle, Australia. His research has been supported by the National Institutes of Health, National Science Foundation, National Academies of Science, as well as by state agencies, private industry and foundations. Dr. Sazonov serves as an Associate Editor for IEEE journal of Biomedical Health Informatics, IEEE sensors and others. He served as EMBC representative on IEEE Sensors Council and on the organizing committees of IEEE BHI/BSN and IEEE Sensors conferences. 

AI for Diabetes Treatment, T1D Patients, Nutrition Estimation, and Glucose Control  

Yao Qin, PhD
Assistant Professor, UC Santa Barbara  
Co-Director, REAL AI Initiative 
Senior Research Scientist, Google Deep Mind 

Yao Qin is an Assistant Professor in the Department of Electrical and Computer Engineering, with an affiliation to the Department of Computer Science at UC Santa Barbara. She is also the co-Director of the REAL AI initiative at UCSB and a Senior Research Scientist at Google DeepMind. She obtained her PhD in Computer Science from UC San Diego working on Artificial Intelligence, particularly AI robustness and safety, which involves safely deploying AI models in the real world. She has over 20 publications in top-tier AI conferences and journals and was recognized as a Rising Star in EECS by MIT in 2020. As a type 1 diabetes (T1D) patient for over 12 years, she is extremely passionate about applying AI techniques for diabetes care, including nutrition estimation, exercise, and closed-loop Automated Insulin Delivery (AID) systems. 

Saturday November 9th, 2024 

AI for Bone Health  

Christopher White, MBBS, PhD, FRACP
Endocrinologist at Prince of Wales Hospital in Randwick, Australia  

Professor White is the Executive Director of Maridulu Budyari Gumal, Sydney Partnership for Health Education Research & Enterprise (SPHERE), where he spearheads collaborative research initiatives. In this role, he directs translational strategies, leveraging his executive expertise to drive impactful outcomes. With a background in medicine and research from Sydney University and UNSW, Chris has excelled in executive positions, including SESLHD Director of Research and Medical Co-Director of the ESCM program of Medicine at the Prince of Wales Hospital. His leadership extends to board positions at Neurosciences Research Australia (NeuRA) and the Health Science Alliance at Randwick, where he orchestrates the integration of research into practice.

Chris has led teams focused on innovative software development for clinical decision-making and contributes to research on diabetes management, readmission risk algorithms, and survivors of childhood cancer fostering collaboration across health precincts. Chris continues to practice as a physician and endocrinologist using knowledge-based systems for reporting and integrating Bone Mineral Density and osteoporosis fracture identification in clinical practice and continues to pursue opportunities that will enhance the management of osteoporosis in primary care. A committed mentor, Chris has nurtured numerous young professionals in their careers, while his contributions as a speaker and author have left a significant mark on the field, with patents for tissue-specific gene expression in bone reflecting his pioneering spirit.

AI for Healthcare in Action: What You Need to Know as a Decision Maker? 

Wuraola Oyewusi  
Data Scientist and AI Technical Instructor 
LinkedIn Learning 

Wuraola Oyewusi is a Data Scientist, Technical Instructor, and Pharmacist, a passionate professional committed to advancing Artificial Intelligence practice. She is a Data and AI Instructor at LinkedIn Learning and previously held roles in AI Research as a Researcher (Data Science and Data Curation) at Imperial College London and Led Research and Innovation at Data Science Nigeria. 

Her research interest is in Natural Language Processing and she has also been in the forefront of the unstructured data application and open source access, especially in the area of health and language. She is the Author and Instructor of the Hand-on Natural Language Processing, Advanced AI: NLP techniques for Clinical Datasets, Hands-On Data Science and AI for Healthcare, Python for Health Sciences and Healthcare, Hands-On Data Annotation: Applied Machine Learning, Python Data Analysis for Healthcare, Generative AI Tools for Productivity and Research, and Machine Learning Fundamentals for Healthcare courses on LinkedIn Learning. She has also contributed to the Springer AI in Medicine Textbook and teaches Tech in Yoruba on YouTube. You can follow her research publications and medium blog.

Artificial Intelligence and Statistical Genetics for Diagnosing Thyroid Cancer

Nikita Pozdeyev, MD, PhD 
Assistant Professor, Biomedical Informatics 
University of Colorado, Anchutz School of Medicine  

Nikita Pozdeyev, MD, PhD, is Assistant Professor with joint appointments at the Department of Biomedical Informatics and the Division of Endocrinology, Diabetes and Metabolism at the University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA. Nikita Pozdeyev is an endocrinologist specializing in the diagnosis and treatment of thyroid diseases, including thyroid cancer. His laboratory uses methods of artificial intelligence, machine learning, and statistical genetics to understand genetic mechanisms of thyroid cancer development and aggressiveness and develop clinical tools for thyroid cancer diagnosis and management.

Gen AI in Clinical Practice: Promise, But Much to Improve

Jeffrey Moon, MD MPH
Assistant Chief Medical Information Officer, University of Pennsylvania

As one of Penn's CMIOs, Jeffrey Moon MD MPH is responsible for investigating and implementing system-wide strategic IT initiatives, with the goal of leveraging technology to improve the practice of medicine and experience of patients. Moon is board certified in Clinical Informatics and Emergency Medicine. He has particular interest in discovering and sharing artificial intelligence applications that improve diagnostics, achieve provider well-being, automate tasks and enhance the EMR experience.

 
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