Artificial Intelligence in Oncology Workshop
Artificial Intelligence in Oncology Workshop
Salt Lake City, UT, USA
Salt Lake City, UT, USA
Submission Deadline: June 14, 2024
Submission Deadline: June 14, 2024
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Welcome to the Artificial Intelligence in Oncology Workshop, an expert led event dedicated to AI applications in oncology, fostering innovation and improving patient outcomes.
Welcome to the Artificial Intelligence in Oncology Workshop, an expert led event dedicated to AI applications in oncology, fostering innovation and improving patient outcomes.
OVERVIEW
The workshop aims to foster collaborative efforts, share insights, and pave the way for a future where AI plays a pivotal role in advancing cancer care.
FORMAT
The workshop will be full day with two 15-minute coffee and 1-hour lunch breaks featuring two keynote speakers (1-hour talks in the morning and afternoon). The rest of the talks will be 45 min. We will have two panels of speakers at the end of the morning and afternoon sessions to allow more discussion time with the audience.
TOPICS
Topics include but not limited to
Topics include but not limited to
- Machine learning based predictive models using genomic, EHR and imaging data in oncology
- Natural language processing (NLP) techniques for mining information from real-world oncology data including EHR
- Large language models (LLMs) applying real-world data in oncology research
- AI applications in radiology and radiogenomics
- Image analysis for tumor detection and classification
- Machine learning techniques for genomic data interpretation
- AI-driven drug discovery and development in oncology
- Innovative clinical trials design using AI/ML
- Patient clinical trial matching using AI/ML
- Development and applications of AI/ML in digital oncology
- Leveraging and learning from real-world data to advance cancer research
KEYNOTE SPEAKERS
ORGANIZING COMMITTEE
Ece Uzun, MS, PhD, FAMIA
Brown University
Lead Chair
Aik Choon Tan, PhD
University of Utah
Co-Chair
Joseph Finkelstein, MD, PhD, FAMIA
University of Utah
Co-Chair
Manish Kohli, MD
University of Utah
Co-Chair
JOURNALS READY TO REVIEW SUBMITTED PAPERS
A theme issue, "AI in oncology" will created in JMIR Bioinformatics and Biotechnology with the papers submitted to the workshop. The submission deadline will be the same as the workshop submission deadline.
In order to be considered for simultaneous publication in JCO Clinical Cancer Informatics or another ASCO family journal, papers are required to be submitted by May 15th. Submitted papers will undergo standard rigorous peer review with decisions rendered in an expedited fashion.
The submission deadline for JCO CCI is May 22, 2024
PROGRAM
PROGRAM
Alpine East Room
Alpine East Room
8:30am-8:35am: Introduction and Welcome
8:35am-9:15am: Keynote
Zhongming Zhao, The University of Texas Health Science Center at Houston
Computational approaches for druggable mutations and drug response prediction
9:15am-9:45am: Zhicheng Jiao, The Warren Alpert Medical School of Brown University
Combining radiomics with miRNA-based liquid biopsy for noninvasive, less variable clinical outcome prediction of glioblastoma
9:45am-10:00am: Lorrayya Williams, Meharry Medical College
Virus Integration Site Detection in Tumor Genomes Using Deep Learning
10:00am-10:15am: Coffee break
10:15am-10:45am: Chun-Chia Chen, Chung Shan Medical University
Prediction Models for Recurrent Gastric Cancer by Ranger with features selection using rank aggregation
10:45am-11:15am: Eric Carver, Brown University/Rhode Island Hospital
Investigation of Radiomic Feature Normalizations, Feature Selection, and Modeling
11:15am-11:45am: Jiarui Yao, Boston Children’s Hospital
Extracting Systemic Anticancer Therapy Timelines from Electronic Medical Records using Large Language Models
11:45am-12:15pm: Nic Frisk, University of Rhode Island
Cancer-specific selection intensity outperforms impact scores as inputs to predictive models across diverse clinical features and disease type
12:15pm-1:30pm: Lunch break
1:30pm-2:30pm: Keynote
Young Juhn, Mayo Clinic
The HOUSES Platform: Groundbreaking Social Determinants of Health Metric & A Digital Biomarker in Cancer Care and Research
2:30pm-3:00pm: Aref Smiley, University of Utah
Predicting Chemotherapy Symptom Escalation Using Artificial Intelligence
3:00pm:-3:30pm: Muddassar Farooq, CureMD
An AI Clinical Governance Assistant for Ensuring Compliance of Cancer Treatments with the NCCN Guidelines
3:30-3:45: Coffee break
3:45pm-4:15pm: Wanting Cui, University of Utah
Predicting Prostate Cancer Diagnosis Using Healthcare Utilization Patterns: A Machine Learning Approach with Real-World Data
4:15pm-4:45pm: Ac Tan, University of Utah
NuKit De-array and Alignment: Parameter-Free and automatic Tissue Microarray image data analysis pipeline
4:45pm-5:15pm: Ece Uzun, The Warren Alpert Medical School of Brown University
LUNAR: Predicting Recurrence of Lower-Grade Glioma with Machine Learning
5:15pm-5:45pm: Muddassar Farooq, CureMD
Extracting Breast Cancer Phenotypes from Clinical Notes: Comparing LLMs with Classical Ontology Methods
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