Narges Ahmidi

Narges Ahmidi

Johns Hopkins University

H-index: 14

North America-United States

About Narges Ahmidi

Narges Ahmidi, With an exceptional h-index of 14 and a recent h-index of 11 (since 2020), a distinguished researcher at Johns Hopkins University, specializes in the field of Computer Science, Machine Learning, Health Care, Medical Robotics.

His recent articles reflect a diverse array of research interests and contributions to the field:

Analysis of Missingness Scenarios for Observational Health Data

Delineating morbidity patterns in preterm infants at near-term age using a data-driven approach

Assessable and interpretable sensitivity analysis in the pattern graph framework for nonignorable missingness mechanisms

Evaluation of Active Feature Acquisition Methods for Static Feature Settings

Correlation Between Early Trends of a Prognostic Biomarker and Overall Survival in Non–Small-Cell Lung Cancer Clinical Trials

Robust prediction under missingness shifts

Partially-Specified Causal Simulations

What about the Latent Space? The Need for Latent Feature Saliency Detection in Deep Time Series Classification

Narges Ahmidi Information

University

Position

___

Citations(all)

1494

Citations(since 2020)

1005

Cited By

961

hIndex(all)

14

hIndex(since 2020)

11

i10Index(all)

15

i10Index(since 2020)

12

Email

University Profile Page

Google Scholar

Narges Ahmidi Skills & Research Interests

Computer Science

Machine Learning

Health Care

Medical Robotics

Top articles of Narges Ahmidi

Analysis of Missingness Scenarios for Observational Health Data

2024/4/5

Narges Ahmidi
Narges Ahmidi

H-Index: 13

Delineating morbidity patterns in preterm infants at near-term age using a data-driven approach

BMC pediatrics

2024

Alida Kindt
Alida Kindt

H-Index: 7

Narges Ahmidi
Narges Ahmidi

H-Index: 13

Assessable and interpretable sensitivity analysis in the pattern graph framework for nonignorable missingness mechanisms

Statistics in Medicine

2023/12/20

Narges Ahmidi
Narges Ahmidi

H-Index: 13

Mathias Drton
Mathias Drton

H-Index: 24

Evaluation of Active Feature Acquisition Methods for Static Feature Settings

arXiv preprint arXiv:2312.03619

2023/12/6

Ilya Shpitser
Ilya Shpitser

H-Index: 22

Narges Ahmidi
Narges Ahmidi

H-Index: 13

Correlation Between Early Trends of a Prognostic Biomarker and Overall Survival in Non–Small-Cell Lung Cancer Clinical Trials

JCO Clinical Cancer Informatics

2023/11

Narges Ahmidi
Narges Ahmidi

H-Index: 13

Tim Becker
Tim Becker

H-Index: 5

Robust prediction under missingness shifts

2023/10/13

Patrick Rockenschaub
Patrick Rockenschaub

H-Index: 3

Narges Ahmidi
Narges Ahmidi

H-Index: 13

Partially-Specified Causal Simulations

arXiv preprint arXiv:2309.10514

2023/9/19

Narges Ahmidi
Narges Ahmidi

H-Index: 13

What about the Latent Space? The Need for Latent Feature Saliency Detection in Deep Time Series Classification

Machine Learning and Knowledge Extraction

2023/5/18

Narges Ahmidi
Narges Ahmidi

H-Index: 13

Post-hoc Saliency Methods Fail to Capture Latent Feature Importance in Time Series Data

2023/5/4

Narges Ahmidi
Narges Ahmidi

H-Index: 13

Proteomics reveals antiviral host response and NETosis during acute COVID-19 in high-risk patients

Biochimica et Biophysica Acta (BBA)-Molecular Basis of Disease

2023/2/1

Entwicklung und Zertifizierung klinischer KI-Software

2023

Narges Ahmidi
Narges Ahmidi

H-Index: 13

Leveraging machine learning to predict 30-day hospital readmission after cardiac surgery

The Annals of Thoracic Surgery

2022/12/1

Longitudinal assessment of ROPRO as an early indicator of overall survival in oncology clinical trials: a retrospective analysis

medRxiv

2022/10/12

Artificial Intelligence in action for our well-being: How the new technology finds its place in the medical sector

Digitale Welt

2022/10

Narges Ahmidi
Narges Ahmidi

H-Index: 13

Evaluation of Active Feature Acquisition Methods under Missing Data

2022/9/29

Ilya Shpitser
Ilya Shpitser

H-Index: 22

Narges Ahmidi
Narges Ahmidi

H-Index: 13

Improved macro-and micronutrient supply for favorable growth and metabolomic profile with standardized parenteral nutrition solutions for very preterm infants

Nutrients

2022/9/21

Proteome reveals antiviral host response and NETosis during acute COVID-19 in high-risk patients (preprint)

2022

Early-, late-, and very late-term prediction of target lesion failure in coronary artery stent patients: An international multi-site study

Applied Sciences

2021/7/29

Narges Ahmidi
Narges Ahmidi

H-Index: 13

Artificial intelligence for prognostic scores in oncology: a benchmarking study

Frontiers in Artificial Intelligence

2021/4/16

Tim Becker
Tim Becker

H-Index: 5

Narges Ahmidi
Narges Ahmidi

H-Index: 13

See List of Professors in Narges Ahmidi University(Johns Hopkins University)