Submissions from 2025
Predicting Post-Heart Transplant Mortality Using Advanced Machine Learning Techniques, Javier Jimenez, Muni Rubens, Anshul Saxena, Daniel Koerfer, and Sandra Chaparro
Assessing the Impact of Obesity on Postoperative outcomes in Renal Cell Carcinoma using Machine Learning, Atulya A. Khosla, Yanija Zhang, Mukesh Roy, Venkataraghavan Ramamoorthy, and Anshul Saxena
Development and Validation of a Machine Learning Prediction Model for Textbook Outcome in Liver Surgery: Results From a Multicenter, International Cohort, Nuria Lluis Vinas
Delta-Radiomics Using Machine Learning Classifiers With Auxiliary Data Sets to Predict Disease Progression During Magnetic Resonance-Guided Radiotherapy in Adrenal Metastases, Kathryn Mittauer, Tugce Kutuk, and Rupesh Kotecha
Multifactorial Approach to Falls Prevention with Inclusion of Morse Fall Scores & Artificial Intelligence Technology, Ruth Navarro, Andrea Tilleman, Lupe Almaguer, Grace Aguilera, Kristina Diaz-Rivas, Yesenia Perez, Alex Vanegas, Jessica Amigot, and Janet Ruiz
Multifactorial Approach to Falls Prevention with Inclusion of Morse Fall Scores & Artificial Intelligence Technology, Ruth Navarro, Andrea Tilleman, Lupe Almaguer, Grace Aguilera, Kristina Diaz-Rivas, Yesenia Perez, Alex Vanegas, Jessica Amigot, and Janet Ruiz
Multifactorial Approach to Falls Prevention with Inclusion of Morse Fall Scores & Artificial Intelligence Technology, Ruth Navarro, Andrea Tilleman, Lupe Almaguer, Grace Aguilera, Kristina Diaz-Rivas, Yesenia Quintero, Alex Vanegas, and Jessica Amigot
Leveraging Artificial Intelligence to Adjust Staffing Levels in the Emergency Department, Marisel Perigo and Haydee Fernandez
Leveraging Artificial Intelligence to Adjust Staffing Levels in the Emergency Department, Marisel Perigo and Haydee Fernandez
Leveraging Artificial Intelligence to Adjust Staffing Levels in the Emergency Department, Marisel Perigo and Haydee Fernandez
Role of artificial intelligence in predicting the renal function after nephrectomy in renal cell carcinoma: a systematic review and meta-analysis, Mohamed Javid Raja Iyub, Mukesh Roy, Muni Rubens, and Murugesan Manoharan
Multifactorial Approach to Falls Prevention with Morse Fall Scores and Artificial Intelligence (AI) Technology, Melanie Sosa and Andrea Tilleman
Estimating Algorithmic Fairness and Bias in Predicting Sleeping Difficulties Using Artificial Intelligence and Machine Learning, Sonal Yadav, Yanija Zhang, Md Ashfaq Ahmed, Vedant Tripathi, Venkataraghavan Ramamoorthy, Mukesh Roy, Muni Rubens, and Anshul Saxena
Assessment of outcomes and machine Learning-based models to predict local failure risk following stereotactic radiosurgery for small brain metastases, Sreenija Yarlagadda, Yanjia Zhang, Anshul Saxena, Tugce Kutuk, Ranjini Tolakanahalli, Haley Appel, Roberto Herrera, Matthew Hall, Robert Press, D Jay Wieczorek, Cecilia Lee, Tatiana Bejarano, Michael McDermott, Alonso Gutierrez, Minesh Mehta, and Rupesh Kotecha
Integrating Machine Learning into Healthcare: Enhancing Predictive Analytics for Patient Outcomes, Samira Zad and Kianoosh Boroojeni
Submissions from 2024
Application of Machine Learning Techniques for Predicting Mortality and Readmission After Coronary Artery Bypass Grafting: A Systematic Review and Meta-Analysis, Md Ashfaq Ahmed, Yanjia Zhang, Zhenwei Zhang, Venkataraghavan Ramamoorthy, Mukesh Roy, Anshul Saxena, Muni Rubens, Sandra Chaparro, and Javier Jimenez
Transforming Healthcare Education: Integrating Conversational Artificial Intelligence into Nursing Simulation, Henry Henao, Mark Fonseca, and Alexandre Torre
A Machine Learning Approach To Predict Mortality Due To Immune-Mediated Thrombotic Thrombocytopenic Purpura, Camila Masias
A machine learning approach to predict mortality due to immune-mediated thrombotic thrombocytopenic purpura, Camila Masias Castanon
Leveraging Artificial Intelligence to Adjust Staffing Levels in the Emergency Department, Marisel Perigo and Haydee Fernandez
Submissions from 2023
Improving ICU Risk Predictive Models Through Automation Designed for Resiliency Against Documentation Bias, Donna Lee Armaignac and Eduardo Martinez-Dubouchet
Artificial intelligence in laparoscopic simulation: a promising future for large-scale automated evaluations, Domenech Asbun
A machine learning based-personalized plan selection methodology for reducing skin toxicity in proton pencil beam scanning, Michael Kasper and Suresh Rana
Supervised machine learning algorithms demonstrate proliferation index correlates with long-term recurrence after complete resection of WHO grade I meningioma, Michael McDermott
Prediction of Non-home Discharge After Total Shoulder Replacement Using Machine Learning Methods: A National Surgical Quality Improvement Program Study (2019-2020), Luis A. Vargas, Jonas Ravich, Nicolette Schurhoff, Matthias Schurhoff, Md Ashfaq Ahmed, Zhenwei Zhang, Yanija Zhang, Anshul Saxena, and Gautam Yagnik
Submissions from 2022
Insights From Meta-analysis Of Studies Using Machine Learning To Predict Mortality Or Acute Kidney Injury After Coronary Artery Bypass Graft, Md Ashfaq Ahmed, Zhenwei Zhang, Peter McGranaghan, Muni Rubens, Venkataraghavan Ramamoorthy, Anshul Saxena, Sandra Chaparro, Javier Jimenez, and Emir Veledar
The Emerging Role of Artificial Intelligence in Gastrointestinal Endoscopy: A Review, Andres Gelrud
Application Of Machine Learning In Predicting Clinical Adverse Events After Transcatheter Aortic Valve Replacement Procedure: Insights From A Systematic Review And Meta-analysis Of Studies, Peter McGranaghan, Muni Rubens, Md Ashfaq Ahmed, Zhenwei Zhang, Anshul Saxena, and Emir Veledar
The Impact of Technologist Mammographic Positioning Training as Measured by Artificial Intelligence, Kathy Schilling
Insights From Meta-analysis Of Studies Using Machine Learning To Predict Mortality, Readmission, Or Other Outcomes Among Heart Failure Patients, Zhenwei Zhang, Md Ashfaq Ahmed, Peter McGranaghan, Muni Rubens, Venkataraghavan Ramamoorthy, Anshul Saxena, Sandra Chaparro, Javier Jimenez, and Emir Veledar
Submissions from 2021
CLRM-01. MACHINE LEARNING TO UNCOVER SIGNATURES OF VULNERABILITY IN GLIOBLASTOMA UMBRELLA SIGNATURE TRIAL (GUST), Manmeet Ahluwalia
Natural Language Processing and Machine Learning for Detection of Respiratory Illness by Chest CT Imaging and Tracking of COVID-19 Pandemic in the US, Ricardo Cury, Robson Macedo, and Juan Batlle
Opportunities for Integration of Artificial Intelligence into Stereotactic Radiosurgery Practice, Rupesh Kotecha
Machine Learning Adds to Clinical and CAC Assessments in Predicting 10-Year CHD and CVD Deaths, Khurram Nasir
Heterotypic clustering of circulating tumor cells and circulating cancer-associated fibroblasts facilitates breast cancer metastasis, Ana Sandoval Leon
Natural language processing (NLP) and machine learning (ML) model for predicting CMS OP-35 categories among patients receiving chemotherapy, Anshul Saxena, Peter McGranaghan, Muni Rubens, Joseph Salami, Raees Tonse, Amanda Lindeman, Michelle Keller, Paul Lindeman, and Emir Veledar
Submissions from 2020
A Boosted Ensemble Algorithm for Determination of Plaque Stability in High-Risk Patients on Coronary CTA, Ricardo Cury
Abstract 178: Predicting Employee Health and Cost: Application of Machine Learning on Employee Health Claims Data, Insights, and Possibilities, Anshul Saxena, Sankalp Das, Muni Rubens, Joseph Salami, Chintan Bhatt, Tian Tian, Peter McGranaghan, Louis Gidel, and Emir Veledar PhD
Development of an Advanced Analytics DataMart for Machine Learning, Effectiveness Research, and Population Health Trends, Carlos Valle, Lourdes Rojas, Chintan Bhatt, Eduardo Martinez-DuBouchet.se-ccu-icu, Lisa-Mae Williams, Don Parris, Louis Gidel, and Donna Lee Armaignac
Submissions from 2019
Development of an Advanced Analytics DataMart for Machine Learning, Effectiveness Research, and Population Health Trends, Carlos Valle, Lourdes Rojas, Chintan Bhatt, Eduardo Martinez-DuBouchet.se-ccu-icu, Lisa-Mae Williams, Don Parris, Louis Gidel, and Donna Lee Armaignac
Submissions from 2018
Towards phenotyping stroke: Leveraging data from a large-scale epidemiological study to detect stroke diagnosis, Felipe De Los Rios La Rosa
Participatory methods to support team science development for predictive analytics in health, Paul Di Capua
Coronary artery disease reporting and data system (CAD-RADSTM): Inter-observer agreement for assessment categories and modifiers, Christopher Maroules and Ricardo Cury
Big Data and Machine Learning: A Resident's Perspective of the 2016 Intersociety Conference, Alexander Misono
Synoptic Reporting: Evidence-Based Review and Future Directions, Andrew Renshaw, Mercy Mena-Allauca, and Edwin Gould
Abstract 17123: Hierarchical Clustering in 2014 Medical Expenditure Panel Survey (MEPS) to Examine the Cost of Events Related to Acute Myocardial Infraction (AMI) and Hypertension (HTN), Anshul Saxena and Emir Veledar
Submissions from 2017
Study of young patients with myocardial infarction: Design and rationale of the YOUNG-MI Registry, Khurram Nasir
Submissions from 2015
A probabilistic approach for pediatric epilepsy diagnosis using brain functional connectivity networks, Alberto Pinzon Ardila and Sergio Gonzalez-Arias
Pediatric epilepsy: Clustering by functional connectivity using phase synchronization, Alberto Pinzon Ardila and Sergio Gonzalez-Arias