RM
Rameshbabu Manyam
Emory University, University of Tennessee at Knoxville, Indian Institute of Technology BHU, National Institute of Technology Warangal, Truist Atlanta
Research areas: Medicine · Surgery · Artificial Intelligence in Healthcare · Cardiac and Coronary Surgery Techniques · Cardiac, Anesthesia and Surgical Outcomes
0000-0003-0602-9632
Employment
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Emory University Assistant Professor2022 - Present
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Emory University Data Scientist, Sr.2016 - 2022
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University of Tennessee Data Architect, Sr.2015 - 2016
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Truist Atlanta Data Architect2014 - 2015
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Kennesaw State University Data Warehouse Manager2011 - 2014
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Georgia Department of Transportation Programmer/DB Analyst, Sr.; IT Architect2003 - 2010
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Defence Research and Development Organisation Research Scientist1993 - 2000
Education
- ? - 1993
- ? - 1991
Projects & Funding
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Pregnancy in the Age of Artificial Intelligence (AI): Designing an AI-Companion Prenatal Education and Social Support Tool for First-Time Expectant Parents Emory University Rollins School of Public Health2026 - 2027
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Developing a Scalable and interpretable machine learning-powered risk model to evaluate risk factors for interhospital transfer and early mortality after interhospital transfer among older patients in Georgia Georgia Clinical & Translational Science Alliance2026 - 2027
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The LABOR Study: Leveraging Anesthesia-Based Obstetric Risk Assessment for Maternal Safety American Association of Nurse Anesthesiologye2025 - 2026
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Emory Innovation Grant Emory University2023 - Present
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Multimodal Assessment of Near-term Risk Processes for Suicide Ideation and Behavior National Institute of Mental Health2019 - 2025
Publications (29)
- RT10 | Teaching Statistical Programming in the Era of Generative AI: What Should Change, What Shouldn't, and Why? Save
- A Calibrated Machine Learning Ensemble for Predicting Postoperative Pneumonia After Coronary Artery Bypass Grafting Save
- Interpretable machine learning risk model to predict readmission after coronary artery bypass grafting Save
- General Anesthesia and Severe Maternal Morbidity Among Nulliparous Women: nuMoM2b Cohort Save
- Supervised Machine Learning for Severe Maternal Morbidity Prediction Using Clinician-Curated Obstetric Anesthesia Variables in the nuMoM2b Cohort Save
- Reply: Preoperative prediction of failure to rescue after coronary artery bypass grafting Save
- Interpretable Artificial Intelligence Risk Model to Predict Readmission after Coronary Artery Bypass Grafting Save
- RF7. Interpretable Artificial Intelligence Risk Model to Predict Readmission after Coronary Artery Bypass Grafting Save
- 435 Discovering novel atrial fibrillation phenogroups: A multi-algorithm approach using real-world claims data Save
- Interpretable Artificial Intelligence-enabled Risk Model to Predict Pneumonia after Coronary Artery Bypass Grafting Save
- Interpretable artificial intelligence for predicting blood transfusion after surgery for femoral shaft fractures: A retrospective analysis Save
- Overlap weighting versus propensity score matching in a rare obstetric exposure: anesthesia modality and severe maternal morbidity in the nuMoM2b cohort Save
- Predicting Risk Factors for Suicidal Ideation using Interpretable Artificial Intelligence Methods Save
- Interpretable Artificial Intelligence to Predict Preoperative Risk Factors for Failure to Rescue after Coronary Artery Bypass Grafting. Save
- Artificial intelligence for predicting 30-day mortality after surgery for femoral shaft fractures: A retrospective study Save
- Correlation of Inflammatory Biomarkers and IgG4 Antibodies with Malaria in Cameroon’s Buea Municipality Children Save
- Interpretable Machine Learning to Predict Blood Transfusion after Surgery for Femoral Shaft Fractures Save
- Unraveling the Potential of AI for Predictive Analytics in Healthcare Save
- Determinants of Under-Immunization Among Children Between 0 and 59 Months in Buea Municipality, South Western Cameroon: Implications for National Immunization Campaign Save
- AI-driven Models with Effective Feature Selection Accurately Predict ICU Admission after Laparoscopic Cholecystectomy Save