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Books from 2024

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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

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Transforming Healthcare Education: Integrating Conversational Artificial Intelligence into Nursing Simulation, Henry Henao, Mark Fonseca, and Alexandre Torre

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Leveraging Artificial Intelligence to Adjust Staffing Levels in the Emergency Department, Marisel Perigo and Haydee Fernandez

Submissions from 2023

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Improving ICU Risk Predictive Models Through Automation Designed for Resiliency Against Documentation Bias, Donna Lee Armaignac and Eduardo Martinez-Dubouchet

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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

Real world breast cancer screening performance with digital breast tomosynthesis before and after implementation of an artificial intelligence detection system, Kathy Schilling

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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

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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

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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

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Opportunities for Integration of Artificial Intelligence into Stereotactic Radiosurgery Practice, Rupesh Kotecha

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Machine Learning Adds to Clinical and CAC Assessments in Predicting 10-Year CHD and CVD Deaths, Khurram Nasir

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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

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A Boosted Ensemble Algorithm for Determination of Plaque Stability in High-Risk Patients on Coronary CTA, Ricardo Cury

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Machine learning of clinical variables and coronary artery calcium scoring for the prediction of obstructive coronary artery disease on coronary computed tomography angiography: analysis from the CONFIRM registry, Ricardo Cury

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Effectiveness of Radiofrequency Ablation in the Treatment of Painful Osseous Metastases: A Correlation Meta-Analysis with Machine Learning Cluster Identification, Minesh Mehta

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

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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

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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

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Maximization of the usage of coronary CTA derived plaque information using a machine learning based algorithm to improve risk stratification; insights from the CONFIRM registry, Ricardo Cury

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Towards phenotyping stroke: Leveraging data from a large-scale epidemiological study to detect stroke diagnosis, Felipe De Los Rios La Rosa

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Participatory methods to support team science development for predictive analytics in health, Paul Di Capua

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Coronary artery disease reporting and data system (CAD-RADSTM): Inter-observer agreement for assessment categories and modifiers, Christopher Maroules and Ricardo Cury

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Big Data and Machine Learning: A Resident's Perspective of the 2016 Intersociety Conference, Alexander Misono

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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

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Machine learning for prediction of all-cause mortality in patients with suspected coronary artery disease: a 5-year multicentre prospective registry analysis, Ricardo Cury

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Study of young patients with myocardial infarction: Design and rationale of the YOUNG-MI Registry, Khurram Nasir

Submissions from 2015

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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