Ben Lengerich

Ben Lengerich

Massachusetts Institute of Technology

H-index: 13

North America-United States

About Ben Lengerich

Ben Lengerich, With an exceptional h-index of 13 and a recent h-index of 12 (since 2020), a distinguished researcher at Massachusetts Institute of Technology, specializes in the field of ML, AI, Medical Informatics, Computational Genomics.

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

Interpretable Predictive Models to Understand Risk Factors for Maternal and Fetal Outcomes

Data Science with LLMs and Interpretable Models

Preterm preeclampsia prediction using intelligible machine learning

LLMs understand glass-box models, discover surprises, and suggest repairs

Contextualized Networks Reveal Heterogeneous Transcriptomic Regulation in Tumors at Sample-Specific Resolution

Unique insights into risk factors for antepartum stillbirth using explainable AI

Integrating single-cell RNA-seq datasets with substantial batch effects

Predicting severe maternal morbidity at admission for delivery using intelligible machine learning

Ben Lengerich Information

University

Position

___

Citations(all)

2613

Citations(since 2020)

2421

Cited By

983

hIndex(all)

13

hIndex(since 2020)

12

i10Index(all)

13

i10Index(since 2020)

12

Email

University Profile Page

Massachusetts Institute of Technology

Google Scholar

View Google Scholar Profile

Ben Lengerich Skills & Research Interests

ML

AI

Medical Informatics

Computational Genomics

Top articles of Ben Lengerich

Title

Journal

Author(s)

Publication Date

Interpretable Predictive Models to Understand Risk Factors for Maternal and Fetal Outcomes

Journal of Healthcare Informatics Research

Tomas M Bosschieter

Zifei Xu

Hui Lan

Benjamin J Lengerich

Harsha Nori

...

2024/3

Data Science with LLMs and Interpretable Models

arXiv preprint arXiv:2402.14474

Sebastian Bordt

Ben Lengerich

Harsha Nori

Rich Caruana

2024/2/22

Preterm preeclampsia prediction using intelligible machine learning

American Journal of Obstetrics & Gynecology

Tomas M Bosschieter

Zifei Xu

Hui Lan

Benjamin Lengerich

Harsha Nori

...

2023/1/1

LLMs understand glass-box models, discover surprises, and suggest repairs

arXiv preprint arXiv:2308.01157

Benjamin J Lengerich

Sebastian Bordt

Harsha Nori

Mark E Nunnally

Yin Aphinyanaphongs

...

2023/8/2

Contextualized Networks Reveal Heterogeneous Transcriptomic Regulation in Tumors at Sample-Specific Resolution

bioRxiv

Caleb N Ellington

Benjamin J Lengerich

Thomas BK Watkins

Jiekun Yang

Hanxi Xiao

...

2023

Unique insights into risk factors for antepartum stillbirth using explainable AI

American Journal of Obstetrics & Gynecology

Tomas M Bosschieter

Hui Lan

Zifei Xu

Benjamin Lengerich

Harsha Nori

...

2023/1/1

Integrating single-cell RNA-seq datasets with substantial batch effects

bioRxiv

Karin Hrovatin

Amir Ali Moinfar

Alejandro Tejada Lapuerta

Luke Zappia

Ben Lengerich

...

2023/11/5

Predicting severe maternal morbidity at admission for delivery using intelligible machine learning

American Journal of Obstetrics & Gynecology

Zifei Xu

Tomas M Bosschieter

Hui Lan

Benjamin Lengerich

Harsha Nori

...

2023/1/1

Contextualized machine learning

arXiv preprint arXiv:2310.11340

Benjamin Lengerich

Caleb N Ellington

Andrea Rubbi

Manolis Kellis

Eric P Xing

2023/10/17

Understanding risk factors for shoulder dystocia using interpretable machine learning

American Journal of Obstetrics & Gynecology

Hui Lan

Tomas M Bosschieter

Zifei Xu

Benjamin Lengerich

Harsha Nori

...

2023/1/1

Contextualized Policy Recovery: Modeling and Interpreting Medical Decisions with Adaptive Imitation Learning

Caleb Ellington

Jannik Deuschel

Ben Lengerich

Yingtao Luo

Pascal Friederich

...

2023/10/13

Death by Round Numbers: Glass-Box Machine Learning Uncovers Biases in Medical Practice

medRxiv

Benjamin J Lengerich

Rich Caruana

Mark E Nunnally

Manolis Kellis

2022/5/1

Executive Function: A Contrastive Value Policy for Resampling and Relabeling Perceptions via Hindsight Summarization?

arXiv preprint arXiv:2204.12639

Chris Lengerich

Ben Lengerich

2022/4/27

Estimating Discontinuous Time-Varying Risk Factors and Treatment Benefits for COVID-19 with Interpretable ML

arXiv preprint arXiv:2211.08991

Benjamin Lengerich

Mark E Nunnally

Yin Aphinyanaphongs

Rich Caruana

2022/11/15

Ten quick tips for deep learning in biology

PLoS computational biology

Benjamin D Lee

Anthony Gitter

Casey S Greene

Sebastian Raschka

Finlay Maguire

...

2022/3/24

Using interpretable machine learning to predict maternal and fetal outcomes

arXiv preprint arXiv:2207.05322

Tomas M Bosschieter

Zifei Xu

Hui Lan

Benjamin J Lengerich

Harsha Nori

...

2022/7/12

Automated interpretable discovery of heterogeneous treatment effectiveness: A COVID-19 case study

Journal of biomedical informatics

Benjamin J Lengerich

Mark E Nunnally

Yin Aphinyanaphongs

Caleb Ellington

Rich Caruana

2022/6/1

Dropout as a regularizer of interaction effects

Benjamin J Lengerich

Eric Xing

Rich Caruana

2022/5/3

Insights into severe maternal morbidity in the NTSV population

American Journal of Obstetrics & Gynecology

Benjamin J Lengerich

Rich Caruana

William B Weeks

Ian Painter

Sydney Spencer

...

2021/2/1

NOTMAD: Estimating Bayesian Networks with Sample-Specific Structures and Parameters

arXiv preprint arXiv:2111.01104

Ben Lengerich

Caleb Ellington

Bryon Aragam

Eric P Xing

Manolis Kellis

2021/11/1

See List of Professors in Ben Lengerich University(Massachusetts Institute of Technology)

Co-Authors

H-index: 147
Manolis Kellis

Manolis Kellis

Massachusetts Institute of Technology

H-index: 114
Eric Xing

Eric Xing

Carnegie Mellon University

H-index: 91
Manuela M. Veloso

Manuela M. Veloso

Carnegie Mellon University

H-index: 84
Sharon Hammes-Schiffer

Sharon Hammes-Schiffer

Yale University

H-index: 23
Willie Neiswanger

Willie Neiswanger

Stanford University

H-index: 19
Maruan Al-Shedivat

Maruan Al-Shedivat

Carnegie Mellon University

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