Suchi Saria
#33,114
Most Influential Person Now
Scientist, machine learning, Johns Hopkins
Suchi Saria's AcademicInfluence.com Rankings
Suchi Sariacomputer-science Degrees
Computer Science
#1655
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#1713
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Algorithms
#204
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#207
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Machine Learning
#273
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#276
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Database
#8366
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#8753
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Computer Science
Suchi Saria's Degrees
- PhD Computer Science Stanford University
- Masters Computer Science Stanford University
- Bachelors Computer Science IIT Delhi
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Why Is Suchi Saria Influential?
(Suggest an Edit or Addition)According to Wikipedia, Suchi Saria is an Associate Professor of Machine Learning and Healthcare at Johns Hopkins University, where she uses big data to improve patient outcomes. She is a World Economic Forum Young Global Leader. From 2022 to 2023, she was an investment partner at AIX Ventures. AIX Ventures is a venture capital fund that invests in artificial intelligence startups.
Suchi Saria's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- Big data in health care: using analytics to identify and manage high-risk and high-cost patients. (2014) (840)
- A targeted real-time early warning score (TREWScore) for septic shock (2015) (456)
- Do no harm: a roadmap for responsible machine learning for health care (2019) (373)
- Using Smartphones and Machine Learning to Quantify Parkinson Disease Severity: The Mobile Parkinson Disease Score (2018) (241)
- Microsoft Cambridge at TREC 13: Web and Hard Tracks (2004) (201)
- Integration of Early Physiological Responses Predicts Later Illness Severity in Preterm Infants (2010) (174)
- Minimum information about clinical artificial intelligence modeling: the MI-CLAIM checklist (2020) (155)
- Reliable Decision Support using Counterfactual Models (2017) (153)
- The Clinician and Dataset Shift in Artificial Intelligence. (2021) (153)
- Preventing Failures Due to Dataset Shift: Learning Predictive Models That Transport (2018) (118)
- Clustering Longitudinal Clinical Marker Trajectories from Electronic Health Data: Applications to Phenotyping and Endotype Discovery (2015) (110)
- From development to deployment: dataset shift, causality, and shift-stable models in health AI. (2019) (100)
- A Framework for Individualizing Predictions of Disease Trajectories by Exploiting Multi-Resolution Structure (2015) (94)
- Developing Predictive Models Using Electronic Medical Records: Challenges and Pitfalls (2013) (90)
- Subtyping: What It is and Its Role in Precision Medicine (2015) (81)
- Can You Trust This Prediction? Auditing Pointwise Reliability After Learning (2019) (76)
- High Frequency Remote Monitoring of Parkinson's Disease via Smartphone: Platform Overview and Medication Response Detection (2016) (71)
- Better medicine through machine learning: What’s real, and what’s artificial? (2018) (70)
- Tutorial: Safe and Reliable Machine Learning (2019) (53)
- Reasoning at the Right Time Granularity (2007) (51)
- A Bayesian Nonparametic Approach for Estimating Individualized Treatment-Response Curves (2016) (50)
- Probabilistic Plan Recognition in Multiagent Systems (2004) (50)
- Scalable Joint Models for Reliable Uncertainty-Aware Event Prediction (2017) (49)
- Measuring Patient Mobility in the ICU Using a Novel Noninvasive Sensor (2017) (46)
- Treatment-Response Models for Counterfactual Reasoning with Continuous-time, Continuous-valued Interventions (2017) (44)
- Consensus Statement on Electronic Health Predictive Analytics: A Guiding Framework to Address Challenges (2016) (44)
- Evaluating Model Robustness and Stability to Dataset Shift (2021) (41)
- Reporting and Implementing Interventions Involving Machine Learning and Artificial Intelligence (2020) (39)
- Prospective, multi-site study of patient outcomes after implementation of the TREWS machine learning-based early warning system for sepsis (2022) (39)
- Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI (2022) (39)
- Learning (predictive) risk scores in the presence of censoring due to interventions (2015) (38)
- Individualized sepsis treatment using reinforcement learning (2018) (36)
- Dissecting an Online Intervention for Cancer Survivors (2015) (35)
- Development and validation of a prediction model for insulin-associated hypoglycemia in non-critically ill hospitalized adults (2018) (34)
- Discovering Deformable Motifs in Continuous Time Series Data (2011) (33)
- Deep Phenotyping of Parkinson’s Disease (2020) (32)
- Convex envelopes of complexity controlling penalties: the case against premature envelopment (2011) (32)
- Counterfactual Normalization: Proactively Addressing Dataset Shift Using Causal Mechanisms (2018) (32)
- Why policymakers should care about “big data” in healthcare (2018) (30)
- Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI (2022) (30)
- Perinatal risk factors for severe injury in neonates treated with whole-body hypothermia for encephalopathy. (2014) (27)
- Metadata Concepts for Advancing the Use of Digital Health Technologies in Clinical Research. (2019) (26)
- Development and Validation of a Machine Learning Model to Predict Near-Term Risk of Iatrogenic Hypoglycemia in Hospitalized Patients (2021) (26)
- Artificial Intelligence for Social Good (2019) (26)
- Correlation of preterm infant illness severity with placental histology. (2016) (24)
- Active Learning for Decision-Making from Imbalanced Observational Data (2019) (23)
- Counterfactual Normalization: Proactively Addressing Dataset Shift and Improving Reliability Using Causal Mechanisms (2018) (22)
- Integrative Analysis using Coupled Latent Variable Models for Individualizing Prognoses (2016) (22)
- 3D Sensing Algorithms Towards Building an Intelligent Intensive Care Unit (2013) (21)
- The Association Between Neighborhood Socioeconomic Disadvantage and Readmissions for Patients Hospitalized With Sepsis (2019) (21)
- An Individualized, Data-Driven Digital Approach for Precision Behavior Change (2020) (20)
- Discovering shared and individual latent structure in multiple time series (2010) (20)
- A $3 Trillion Challenge to Computational Scientists: Transforming Healthcare Delivery (2014) (20)
- Too Many Definitions of Sepsis: Can Machine Learning Leverage the Electronic Health Record to Increase Accuracy and Bring Consensus? (2020) (19)
- Combining Structured and Free-text Data for Automatic Coding of Patient Outcomes. (2010) (18)
- Learning Predictive Models That Transport (2018) (17)
- Factors driving provider adoption of the TREWS machine learning-based early warning system and its effects on sepsis treatment timing (2022) (14)
- A Non-parametric Bayesian Approach for Estimating Treatment-Response Curves from Sparse Time Series (2016) (14)
- Do no harm: a roadmap for responsible machine learning for health care (2019) (13)
- Human–machine teaming is key to AI adoption: clinicians’ experiences with a deployed machine learning system (2022) (13)
- Comparison of Automated Sepsis Identification Methods and Electronic Health Record–based Sepsis Phenotyping: Improving Case Identification Accuracy by Accounting for Confounding Comorbid Conditions (2019) (12)
- Early Detection of Poor Adherers to Statins: Applying Individualized Surveillance to Pay for Performance (2013) (12)
- A Universal Hierarchy of Shift-Stable Distributions and the Tradeoff Between Stability and Performance (2019) (11)
- A bias evaluation checklist for predictive models and its pilot application for 30-day hospital readmission models (2022) (11)
- I-SPEC: An End-to-End Framework for Learning Transportable, Shift-Stable Models (2020) (10)
- Author Correction: Do no harm: a roadmap for responsible machine learning for health care (2019) (9)
- What-If Reasoning with Counterfactual Gaussian Processes (2017) (9)
- Partial Identifiability in Discrete Data With Measurement Error (2020) (8)
- Evaluating Model Robustness to Dataset Shift (2020) (8)
- Learning Models from Data with Measurement Error: Tackling Underreporting (2019) (7)
- An Evolutionary Computation Approach for Optimizing Multilevel Data to Predict Patient Outcomes (2018) (7)
- Deformable Distributed Multiple Detector Fusion for Multi-Person Tracking (2015) (7)
- Development and validation of high definition phenotype-based mortality prediction in critical care units (2021) (6)
- Auditing Pointwise Reliability Subsequent to Training (2019) (6)
- Learning a Severity Score for Sepsis: A Novel Approach based on Clinical Comparisons (2015) (5)
- A unifying causal framework for analyzing dataset shift-stable learning algorithms (2019) (5)
- Digital Endpoints: Definition, Benefits, and Current Barriers in Accelerating Development and Adoption (2021) (5)
- What-If Reasoning using Counterfactual Gaussian Processes (2017) (5)
- Using Machine Learning for Early Prediction of Cardiogenic Shock in Patients with Acute Heart Failure (2021) (5)
- Process Monitoring in the Intensive Care Unit: Assessing Patient Mobility Through Activity Analysis with a Non-Invasive Mobility Sensor (2016) (4)
- Discretizing Logged Interaction Data Biases Learning for Decision-Making (2018) (4)
- Factors associated with physicians’ prescriptions for rheumatoid arthritis drugs not filled by patients (2018) (4)
- Research gaps and opportunities in precision nutrition: an NIH workshop report. (2022) (3)
- Medicine 2032: The future of cardiovascular disease prevention with machine learning and digital health technology (2022) (3)
- Predictors of the start of declining eGFR in patients with systemic lupus erythematosus (2020) (3)
- Development and Validation of ARC, a Model for Anticipating Acute Respiratory Failure in Coronavirus Disease 2019 Patients (2021) (3)
- Should I Include this Edge in my Prediction? Analyzing the Stability-Performance Tradeoff (2019) (3)
- Comparison of Automated Activity Recognition to Provider Observations of Patient Mobility in the ICU. (2019) (3)
- Beyond Low Earth Orbit: Biomonitoring, Artificial Intelligence, and Precision Space Health (2021) (3)
- Machine Learning-Based Automatic Classification of Video Recorded Neonatal Manipulations and Associated Physiological Parameters: A Feasibility Study (2020) (3)
- Will Artificial Intelligence Replace the Movement Disorders Specialist for Diagnosing and Managing Parkinson’s Disease? (2021) (3)
- Sensing Algorithms Towards Building an Intelligent Intensive Care Unit (2013) (2)
- Using Causal Inference to Estimate What-if Outcomes for Targeting Treatments (2016) (2)
- Counterfactual Gaussian Processes for Reliable Decision-making and What-if Reasoning (2017) (1)
- 121: FEASIBILITY OF A NON-INVASIVE SENSOR FOR MEASURING ICU PATIENT MOBILITY (2014) (1)
- Beyond Low Earth Orbit: Biological Research, Artificial Intelligence, and Self-Driving Labs (2021) (1)
- Trading-Off Cost of Deployment Versus Accuracy in Learning Predictive Models (2016) (1)
- THE STABILITY AND ACCURACY TRADEOFF UNDER DATASET SHIFT: A CAUSAL GRAPHICAL ANALYSIS (2021) (1)
- The Impact of Time Series Length and Discretization on Longitudinal Causal Estimation Methods. (2020) (1)
- Biological research and self-driving labs in deep space supported by artificial intelligence (2023) (1)
- Using counterfactual queries to improve models for decision-support (2018) (1)
- Evaluating Adoption, Impact, and Factors Driving Adoption for TREWS, a Machine Learning-Based Sepsis Alerting System (2021) (1)
- The Hierarchy of Stable Distributions and Operators to Trade Off Stability and Performance (2019) (1)
- Biomonitoring and precision health in deep space supported by artificial intelligence (2023) (1)
- 1405: ASSESSING CLINICAL USE AND PERFORMANCE OF A MACHINE LEARNING SEPSIS ALERT FOR SEX AND RACIAL BIAS (2021) (1)
- A Probabilistic Graphical Model for Individualizing Prognosis in Chronic, Complex Diseases (2015) (1)
- Individualized sepsis treatment using reinforcement learning (2018) (0)
- Publisher Correction: Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI (2022) (0)
- Learning Treatment-Response Models from Multivariate Longitudinal Data (2017) (0)
- Delivering Precision Behavior Change Through Digital Medicine (2018) (0)
- Predictive Analytics in Healthcare (HPA): Considerations and Challenges (2014) (0)
- A prospective birth cohort study of maternal prenatal cigarette smoking assessed by self-report and biomarkers on childhood risk of overweight or obesity (2022) (0)
- In-Utero Exposure to Cigarette Smoking on Child Long-Term Risk of Obesity: Concordance of Self-Report, Maternal and Cord Blood Biomarkers (2021) (0)
- Advanced Machine Learning for Healthcare (2016) (0)
- JAWS: Auditing Predictive Uncertainty Under Covariate Shift (2022) (0)
- At the Intersection of Health, Health Care and Policy (2014) (0)
- The digital patient: machine learning techniques for analyzing electronic health record data (2011) (0)
- The adoption of high-sensitivity troponin assays changes clinical interpretation of detectable troponin levels (0)
- Learning (predictive) risk scores in the presence of censoring due to interventions (2015) (0)
- Microsoft Word-nqac237.docx (2022) (0)
- A Novel Computational Approach for Scalable Biomarker Discovery in Autoimmune Diseases (2016) (0)
- 1429: LEAD TIME AND ACCURACY OF TREWS, A MACHINE LEARNING-BASED SEPSIS ALERT (2021) (0)
- Making Health AI Work in the Real World: Strategies, innovations, and best practices for using AI to improve care delivery (2021) (0)
- AI's 10 to Watch (2016) (0)
- Health Affairs High-Cost Patients Big Data In Health Care : Using Analytics To Identify And Manage High-Risk And Escobar (2014) (0)
- Incorporating end-user preferences in predictive models (2016) (0)
- Machine Learning Driven Targeted Real-Time Early Warning System Improves Outcomes in Sepsis (2018) (0)
- Active Learning for Improving Decision-Making from Imbalanced Data (2019) (0)
- A Random Forest Genomic Classifier for Tumor Agnostic Prediction of Response to Anti-PD1 Immunotherapy (2022) (0)
- JAWS: Predictive Inference Under Covariate Shift (2022) (0)
- A Framework for Individualized Prognosis of Disease Trajectories in Complex, Chronic Diseases: Application to Scleroderma, an Autoimmune Disease (2015) (0)
- Addressing the 'coin flip model' and the role of 'process of care' variables in the analysis of TREWS (2022) (0)
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