Nigam H. Shah

ORCID

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 77

Top Venues

CoRR

J. Am. Medical Informatics Assoc.

J. Biomed. Informatics

npj Digit. Medicine

Publications

Alison Callahan, Duncan C. McElfresh, Juan M. Banda, Gabrielle Bunney, Danton Char, Jonathan H. Chen, Conor K. Corbin, Debadutta Dash, Norman L. Downing, Sneha S. Jain, Nikesh Kotecha, Jonathan Masterson, Michelle M. Mello, Keith E. Morse, Srikar Nallan, Abby Pandya, Anurang Revri, Aditya Sharma, Christopher D. Sharp, Rahul Thapa, Michael Wornow, Alaa Youssef, Michael A. Pfeffer, Nigam H. Shah
Standing on FURM ground - A framework for evaluating Fair, Useful, and Reliable AI Models in healthcare systems. CoRR (2024)
Michael Wornow, Avanika Narayan, Krista Opsahl-Ong, Quinn McIntyre, Nigam H. Shah, Christopher Ré
Automating the Enterprise with Foundation Models. CoRR (2024)
Yen Sia Low, Michael L. Jackson, Rebecca J. Hyde, Robert E. Brown, Neil M. Sanghavi, Julian D. Baldwin, C. William Pike, Jananee Muralidharan, Gavin Hui, Natasha Alexander, Hadeel Hassan, Rahul V. Nene, Morgan Pike, Courtney J. Pokrzywa, Shivam Vedak, Adam Paul Yan, Dong-han Yao, Amy R. Zipursky, Christina Dinh, Philip Ballentine, Dan C. Derieg, Vladimir Polony, Rehan N. Chawdry, Jordan Davies, Brigham B. Hyde, Nigam H. Shah, Saurabh Gombar
Answering real-world clinical questions using large language model based systems. CoRR (2024)
Scott L. Fleming, Alejandro Lozano, William J. Haberkorn, Jenelle A. Jindal, Eduardo Pontes Reis, Rahul Thapa, Louis Blankemeier, Julian Z. Genkins, Ethan Steinberg, Ashwin Nayak, Birju S. Patel, Chia-Chun Chiang, Alison Callahan, Zepeng Huo, Sergios Gatidis, Scott J. Adams, Oluseyi Fayanju, Shreya J. Shah, Thomas Savage, Ethan Goh, Akshay S. Chaudhari, Nima Aghaeepour, Christopher D. Sharp, Michael A. Pfeffer, Percy Liang, Jonathan H. Chen, Keith E. Morse, Emma P. Brunskill, Jason A. Fries, Nigam H. Shah
MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records. AAAI (2024)
Michael Wornow, Alejandro Lozano, Dev Dash, Jenelle A. Jindal, Kenneth W. Mahaffey, Nigam H. Shah
Zero-Shot Clinical Trial Patient Matching with LLMs. CoRR (2024)
Michael Wornow, Avanika Narayan, Ben Viggiano, Ishan S. Khare, Tathagat Verma, Tibor Thompson, Miguel Angel Fuentes Hernandez, Sudharsan Sundar, Chloe Trujillo, Krrish Chawla, Rongfei Lu, Justin Shen, Divya Nagaraj, Joshua Martinez, Vardhan Agrawal, Althea Hudson, Nigam H. Shah, Christopher Ré
Do Multimodal Foundation Models Understand Enterprise Workflows? A Benchmark for Business Process Management Tasks. CoRR (2024)
Jenelle A. Jindal, Matthew P. Lungren, Nigam H. Shah
Ensuring useful adoption of generative artificial intelligence in healthcare. J. Am. Medical Informatics Assoc. 31 (6) (2024)
Louis Blankemeier, Joseph Paul Cohen, Ashwin Kumar, Dave Van Veen, Syed Jamal Safdar Gardezi, Magdalini Paschali, Zhihong Chen, Jean-Benoit Delbrouck, Eduardo Pontes Reis, Cesar Truyts, Christian Bluethgen, Malte Engmann Kjeldskov Jensen, Sophie Ostmeier, Maya Varma, Jeya Maria Jose Valanarasu, Zhongnan Fang, Zepeng Huo, Zaid Nabulsi, Diego Ardila, Wei-Hung Weng, Edson Amaro Júnior, Neera Ahuja, Jason Alan Fries, Nigam H. Shah, Andrew Johnston, Robert D. Boutin, Andrew Wentland, Curtis P. Langlotz, Jason Hom, Sergios Gatidis, Akshay S. Chaudhari
Merlin: A Vision Language Foundation Model for 3D Computed Tomography. CoRR (2024)
Michael Wornow, Yizhe Xu, Rahul Thapa, Birju S. Patel, Ethan Steinberg, Scott L. Fleming, Michael A. Pfeffer, Jason A. Fries, Nigam H. Shah
The Shaky Foundations of Clinical Foundation Models: A Survey of Large Language Models and Foundation Models for EMRs. CoRR (2023)
Shih-Cheng Huang, Zepeng Huo, Ethan Steinberg, Chia-Chun Chiang, Matthew P. Lungren, Curtis P. Langlotz, Serena Yeung, Nigam H. Shah, Jason A. Fries
INSPECT: A Multimodal Dataset for Pulmonary Embolism Diagnosis and Prognosis. CoRR (2023)
Yizhe Xu, Agata Foryciarz, Ethan Steinberg, Nigam H. Shah
Clinical utility gains from incorporating comorbidity and geographic location information into risk estimation equations for atherosclerotic cardiovascular disease. J. Am. Medical Informatics Assoc. 30 (5) (2023)
Debadutta Dash, Rahul Thapa, Juan M. Banda, Akshay Swaminathan, Morgan Cheatham, Mehr Kashyap, Nikesh Kotecha, Jonathan H. Chen, Saurabh Gombar, Lance Downing, Rachel Pedreira, Ethan Goh, Angel Arnaout, Garret Kenn Morris, Honor Magon, Matthew P. Lungren, Eric Horvitz, Nigam H. Shah
Evaluation of GPT-3.5 and GPT-4 for supporting real-world information needs in healthcare delivery. CoRR (2023)
Scott L. Fleming, Alejandro Lozano, William J. Haberkorn, Jenelle A. Jindal, Eduardo P. Reis, Rahul Thapa, Louis Blankemeier, Julian Z. Genkins, Ethan Steinberg, Ashwin Nayak, Birju S. Patel, Chia-Chun Chiang, Alison Callahan, Zepeng Huo, Sergios Gatidis, Scott J. Adams, Oluseyi Fayanju, Shreya J. Shah, Thomas Savage, Ethan Goh, Akshay S. Chaudhari, Nima Aghaeepour, Christopher D. Sharp, Michael A. Pfeffer, Percy Liang, Jonathan H. Chen, Keith E. Morse, Emma P. Brunskill, Jason A. Fries, Nigam H. Shah
MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records. CoRR (2023)
Conor K. Corbin, Rob Maclay, Aakash Acharya, Sreedevi Mony, Soumya Punnathanam, Rahul Thapa, Nikesh Kotecha, Nigam H. Shah, Jonathan H. Chen
DEPLOYR: a technical framework for deploying custom real-time machine learning models into the electronic medical record. J. Am. Medical Informatics Assoc. 30 (9) (2023)
Michael Wornow, Elsie Gyang Ross, Alison Callahan, Nigam H. Shah
APLUS: A Python library for usefulness simulations of machine learning models in healthcare. J. Biomed. Informatics 139 (2023)
Karandeep Singh, Nigam H. Shah, Andrew J. Vickers
Assessing the net benefit of machine learning models in the presence of resource constraints. J. Am. Medical Informatics Assoc. 30 (4) (2023)
Alexey Youssef, Michael Pencina, Anshul Thakur, Tingting Zhu, David A. Clifton, Nigam H. Shah
All models are local: time to replace external validation with recurrent local validation. CoRR (2023)
Conor K. Corbin, Rob Maclay, Aakash Acharya, Sreedevi Mony, Soumya Punnathanam, Rahul Thapa, Nikesh Kotecha, Nigam H. Shah, Jonathan H. Chen
DEPLOYR: A technical framework for deploying custom real-time machine learning models into the electronic medical record. CoRR (2023)
Michael Wornow, Yizhe Xu, Rahul Thapa, Birju S. Patel, Ethan Steinberg, Scott L. Fleming, Michael A. Pfeffer, Jason Alan Fries, Nigam H. Shah
The shaky foundations of large language models and foundation models for electronic health records. npj Digit. Medicine 6 (2023)
Daniel Lopez Martinez, Alex Yakubovich, Martin Seneviratne, Ádám D. Lelkes, Akshit Tyagi, Jonas Kemp, Ethan Steinberg, N. Lance Downing, Ron C. Li, Keith E. Morse, Nigam H. Shah, Ming-Jun Chen
Instability in clinical risk stratification models using deep learning. CoRR (2022)
Jonathan Lu, Amelia Sattler, Samantha Wang, Ali Raza Khaki, Alison Callahan, Scott L. Fleming, Rebecca Fong, Benjamin Ehlert, Ron C. Li, Lisa Shieh, Kavitha Ramchandran, Michael Gensheimer, Sarah Chobot, Stephen Pfohl, Siyun Li, Kenny Shum, Nitin Parikh, Priya Desai, Briththa Seevaratnam, Melanie Hanson, Margaret Smith, Yizhe Xu, Arjun Gokhale, Steven Lin, Michael A. Pfeffer, Winifred Teuteberg, Nigam H. Shah
Considerations in the reliability and fairness audits of predictive models for advance care planning. Frontiers Digit. Health 4 (2022)
Stephen R. Pfohl, Yizhe Xu, Agata Foryciarz, Nikolaos Ignatiadis, Julian Genkins, Nigam H. Shah
Net benefit, calibration, threshold selection, and training objectives for algorithmic fairness in healthcare. CoRR (2022)
Daniel Lopez Martinez, Alex Yakubovich, Martin Seneviratne, Ádám D. Lelkes, Akshit Tyagi, Jonas Kemp, Ethan Steinberg, N. Lance Downing, Ron C. Li, Keith E. Morse, Nigam H. Shah, Ming-Jun Chen
Instability in clinical risk stratification models using deep learning. ML4H@NeurIPS (2022)
Kenneth Jung, Sehj Kashyap, Anand Avati, Stephanie Harman, Heather Shaw, Ron Li, Margaret Smith, Kenny Shum, Jacob Javitz, Yohan Vetteth, Tina Seto, Steven C. Bagley, Nigam H. Shah
A framework for making predictive models useful in practice. J. Am. Medical Informatics Assoc. 28 (6) (2021)
Lawrence Bai, Madeleine K. D. Scott, Ethan Steinberg, Laurynas Kalesinskas, Aida Habtezion, Nigam H. Shah, Purvesh Khatri
Computational drug repositioning of atorvastatin for ulcerative colitis. J. Am. Medical Informatics Assoc. 28 (11) (2021)
Stephen R. Pfohl, Agata Foryciarz, Nigam H. Shah
An empirical characterization of fair machine learning for clinical risk prediction. J. Biomed. Informatics 113 (2021)
Alison Callahan, Vladimir Polony, José D. Posada, Juan M. Banda, Saurabh Gombar, Nigam H. Shah
ACE: the Advanced Cohort Engine for searching longitudinal patient records. J. Am. Medical Informatics Assoc. 28 (7) (2021)
Sehj Kashyap, Keith E. Morse, Birju S. Patel, Nigam H. Shah
A survey of extant organizational and computational setups for deploying predictive models in health systems. J. Am. Medical Informatics Assoc. 28 (11) (2021)
Michael Ko, Emma Chen, Ashwin Agrawal, Pranav Rajpurkar, Anand Avati, Andrew Yan-Tak Ng, Sanjay Basu, Nigam H. Shah
Improving hospital readmission prediction using individualized utility analysis. J. Biomed. Informatics 119 (2021)
Birju S. Patel, Ethan Steinberg, Stephen R. Pfohl, Nigam H. Shah
Learning decision thresholds for risk stratification models from aggregate clinician behavior. J. Am. Medical Informatics Assoc. 28 (10) (2021)
Michael Francis Gensheimer, Sonya Aggarwal, Kathryn R. K. Benson, Justin N. Carter, Solomon Henry, Douglas J. Wood, Scott G. Soltys, Steven Hancock, Erqi Pollom, Nigam H. Shah, Daniel T. Chang
Automated model versus treating physician for predicting survival time of patients with metastatic cancer. J. Am. Medical Informatics Assoc. 28 (6) (2021)
Alvina G. Lai, Wai Hoong Chang, Constantinos A. Parisinos, Michail Katsoulis, Ruth M. Blackburn, Anoop D. Shah, Vincent Nguyen, Spiros C. Denaxas, George Davey Smith, Tom R. Gaunt, Krishnarajah Nirantharakumar, Murray P. Cox, Donall Forde, Folkert W. Asselbergs, Steve Harris, Sylvia Richardson, Reecha Sofat, Richard J. B. Dobson, Aroon D. Hingorani, Riyaz Patel, Jonathan Sterne, Amitava Banerjee, Alastair K. Denniston, Simon Ball, Neil J. Sebire, Nigam H. Shah, Graham R. Foster, Bryan Williams, Harry Hemingway
An informatics consult approach for generating clinical evidence for treatment decisions. BMC Medical Informatics Decis. Mak. 21 (1) (2021)
Stephen R. Pfohl, Haoran Zhang, Yizhe Xu, Agata Foryciarz, Marzyeh Ghassemi, Nigam H. Shah
A comparison of approaches to improve worst-case predictive model performance over patient subpopulations. CoRR (2021)
Ethan Steinberg, Kenneth Jung, Jason A. Fries, Conor K. Corbin, Stephen R. Pfohl, Nigam H. Shah
Language models are an effective representation learning technique for electronic health record data. J. Biomed. Informatics 113 (2021)
Stephen R. Pfohl, Agata Foryciarz, Nigam H. Shah
An Empirical Characterization of Fair Machine Learning For Clinical Risk Prediction. CoRR (2020)
Tina Hernandez-Boussard, Selen Bozkurt, John P. A. Ioannidis, Nigam H. Shah
MINIMAR (MINimum Information for Medical AI Reporting): Developing reporting standards for artificial intelligence in health care. J. Am. Medical Informatics Assoc. 27 (12) (2020)
Alison Callahan, Ethan Steinberg, Jason A. Fries, Saurabh Gombar, Birju S. Patel, Conor K. Corbin, Nigam H. Shah
Estimating the efficacy of symptom-based screening for COVID-19. npj Digit. Medicine 3 (2020)
Ron C. Li, Steven M. Asch, Nigam H. Shah
Developing a delivery science for artificial intelligence in healthcare. npj Digit. Medicine 3 (2020)
Jason A. Fries, Ethan Steinberg, Saelig Khattar, Scott L. Fleming, José D. Posada, Alison Callahan, Nigam H. Shah
Trove: Ontology-driven weak supervision for medical entity classification. CoRR (2020)
Ethan Steinberg, Kenneth Jung, Jason A. Fries, Conor K. Corbin, Stephen R. Pfohl, Nigam H. Shah
Language Models Are An Effective Patient Representation Learning Technique For Electronic Health Record Data. CoRR (2020)
Sehj Kashyap, Saurabh Gombar, Steve Yadlowsky, Alison Callahan, Jason A. Fries, Benjamin A. Pinsky, Nigam H. Shah
Measure what matters: Counts of hospitalized patients are a better metric for health system capacity planning for a reopening. J. Am. Medical Informatics Assoc. 27 (7) (2020)
Chunhua Weng, Nigam H. Shah, George Hripcsak
Deep phenotyping: Embracing complexity and temporality - Towards scalability, portability, and interoperability. J. Biomed. Informatics 105 (2020)
Mehr Kashyap, Martin G. Seneviratne, Juan M. Banda, Thomas Falconer, Borim Ryu, Sooyoung Yoo, George Hripcsak, Nigam H. Shah
Development and validation of phenotype classifiers across multiple sites in the observational health data sciences and informatics network. J. Am. Medical Informatics Assoc. 27 (6) (2020)
Adam S. Miner, Albert Haque, Jason A. Fries, Scott L. Fleming, Denise E. Wilfley, G. Terence Wilson, Arnold Milstein, Dan Jurafsky, Bruce A. Arnow, W. Stewart Agras, Li Fei-Fei, Nigam H. Shah
Assessing the accuracy of automatic speech recognition for psychotherapy. npj Digit. Medicine 3 (2020)
Alison Callahan, Jason A. Fries, Christopher Ré, James I Huddleston III, Nicholas J. Giori, Scott L. Delp, Nigam H. Shah
Medical device surveillance with electronic health records. CoRR (2019)
Stephen Pfohl, Ben J. Marafino, Adrien Coulet, Fátima Rodriguez, Latha Palaniappan, Nigam H. Shah
Creating Fair Models of Atherosclerotic Cardiovascular Disease Risk. AIES (2019)
Saurabh Gombar, Alison Callahan, Robert M. Califf, Robert A. Harrington, Nigam H. Shah
It is time to learn from patients like mine. npj Digit. Medicine 2 (2019)
Juan M. Banda, Ashish Sarraju, Fahim Abbasi, Justin Parizo, Mitchel Pariani, Hannah Ison, Elinor Briskin, Hannah Wand, Sébastien Dubois, Kenneth Jung, Seth A. Myers, Daniel J. Rader, Joseph B. Leader, Michael F. Murray, Kelly D. Myers, Katherine Wilemon, Nigam H. Shah, Joshua W. Knowles
Finding missed cases of familial hypercholesterolemia in health systems using machine learning. npj Digit. Medicine 2 (2019)
Stephen R. Pfohl, Tony Duan, Daisy Yi Ding, Nigam H. Shah
Counterfactual Reasoning for Fair Clinical Risk Prediction. MLHC (2019)
Albee Y. Ling, Allison W. Kurian, Jennifer L. Caswell-Jin, George W. Sledge Jr., Nigam H. Shah, Suzanne R. Tamang
A Semi-Supervised Machine Learning Approach to Detecting Recurrent Metastatic Breast Cancer Cases Using Linked Cancer Registry and Electronic Medical Record Data. CoRR (2019)
Daisy Yi Ding, Chloé Simpson, Stephen Pfohl, Dave C. Kale, Kenneth Jung, Nigam H. Shah
The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data. PSB (2019)
Vincent X. Liu, David W. Bates, Jenna Wiens, Nigam H. Shah
The number needed to benefit: estimating the value of predictive analytics in healthcare. J. Am. Medical Informatics Assoc. 26 (12) (2019)
Stephen Pfohl, Tony Duan, Daisy Yi Ding, Nigam H. Shah
Counterfactual Reasoning for Fair Clinical Risk Prediction. CoRR (2019)
Kenneth Jung, Sylvia E. K. Sudat, Nicole Kwon, Walter F. Stewart, Nigam H. Shah
Predicting need for advanced illness or palliative care in a primary care population using electronic health record data. J. Biomed. Informatics 92 (2019)
Anand Avati, Tony Duan, Sharon Zhou, Kenneth Jung, Nigam H. Shah, Andrew Y. Ng
Countdown Regression: Sharp and Calibrated Survival Predictions. UAI (2019)
Alison Callahan, Jason A. Fries, Christopher Ré, James I Huddleston III, Nicholas J. Giori, Scott L. Delp, Nigam H. Shah
Medical device surveillance with electronic health records. npj Digit. Medicine 2 (2019)
Alvin Rajkomar, Eyal Oren, Kai Chen, Andrew M. Dai, Nissan Hajaj, Michaela Hardt, Peter J. Liu, Xiaobing Liu, Jake Marcus, Mimi Sun, Patrik Sundberg, Hector Yee, Kun Zhang, Yi Zhang, Gerardo Flores, Gavin E. Duggan, Jamie Irvine, Quoc Le, Kurt Litsch, Alexander Mossin, Justin Tansuwan, De Wang, James Wexler, Jimbo Wilson, Dana Ludwig, Samuel L. Volchenboum, Katherine Chou, Michael Pearson, Srinivasan Madabushi, Nigam H. Shah, Atul J. Butte, Michael D. Howell, Claire Cui, Gregory S. Corrado, Jeffrey Dean
Scalable and accurate deep learning with electronic health records. npj Digit. Medicine 1 (2018)
Anand Avati, Tony Duan, Kenneth Jung, Nigam H. Shah, Andrew Y. Ng
Countdown Regression: Sharp and Calibrated Survival Predictions. CoRR (2018)
Alvin Rajkomar, Eyal Oren, Kai Chen, Andrew M. Dai, Nissan Hajaj, Peter J. Liu, Xiaobing Liu, Mimi Sun, Patrik Sundberg, Hector Yee, Kun Zhang, Gavin E. Duggan, Gerardo Flores, Michaela Hardt, Jamie Irvine, Quoc V. Le, Kurt Litsch, Jake Marcus, Alexander Mossin, Justin Tansuwan, De Wang, James Wexler, Jimbo Wilson, Dana Ludwig, Samuel L. Volchenboum, Katherine Chou, Michael Pearson, Srinivasan Madabushi, Nigam H. Shah, Atul J. Butte, Michael Howell, Claire Cui, Greg Corrado, Jeff Dean
Scalable and accurate deep learning for electronic health records. CoRR (2018)
Anand Avati, Kenneth Jung, Stephanie Harman, Lance Downing, Andrew Y. Ng, Nigam H. Shah
Improving palliative care with deep learning. BMC Medical Informatics Decis. Mak. 18 (S-4) (2018)
Anand Avati, Stephen Pfohl, Chris Lin, Thao Nguyen, Meng Zhang, Philip Hwang, Jessica Wetstone, Kenneth Jung, Andrew Y. Ng, Nigam H. Shah
Predicting Inpatient Discharge Prioritization With Electronic Health Records. CoRR (2018)
Stephen Pfohl, Ben J. Marafino, Adrien Coulet, Fátima Rodriguez, Latha Palaniappan, Nigam H. Shah
Creating Fair Models of Atherosclerotic Cardiovascular Disease Risk. CoRR (2018)
Jason K. Wang, Jason Hom, Santhosh Balasubramanian, Alejandro Schuler, Nigam H. Shah, Mary K. Goldstein, Michael T. M. Baiocchi, Jonathan H. Chen
An evaluation of clinical order patterns machine-learned from clinician cohorts stratified by patient mortality outcomes. J. Biomed. Informatics 86 (2018)
Daisy Yi Ding, Chloé Simpson, Stephen Pfohl, Dave C. Kale, Kenneth Jung, Nigam H. Shah
The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data. CoRR (2018)
Philip R. O. Payne, Nigam H. Shah, Jessica D. Tenenbaum, Lara Mangravite
Session introduction. PSB (2018)
Anand Avati, Kenneth Jung, Stephanie Harman, Lance Downing, Andrew Y. Ng, Nigam H. Shah
Improving Palliative Care with Deep Learning. CoRR (2017)
Rave Harpaz, William DuMouchel, Martijn J. Schuemie, Olivier Bodenreider, Carol Friedman, Eric Horvitz, Anna Ripple, Alfred Sorbello, Ryen W. White, Rainer Winnenburg, Nigam H. Shah
Toward multimodal signal detection of adverse drug reactions. J. Biomed. Informatics 76 (2017)
Yen S. Low, Aaron C. Daugherty, Elizabeth A. Schroeder, William Chen, Tina Seto, Susan C. Weber, Michael Lim, Trevor Hastie, Maya Mathur, Manisha Desai, Carl Farrington, Andrew A. Radin, Marina Sirota, Pragati Kenkare, Caroline A. Thompson, Peter P. Yu, Scarlett L. Gomez, George W. Sledge, Allison W. Kurian, Nigam H. Shah
Synergistic drug combinations from electronic health records and gene expression. J. Am. Medical Informatics Assoc. 24 (3) (2017)
Philip R. O. Payne, Kun Huang, Nigam H. Shah, Jessica D. Tenenbaum
Open Data for Discovery Science. PSB (2017)
Vibhu Agarwal, Nigam H. Shah
Learning Attributes of Disease Progression from Trajectories of Sparse Lab Values. PSB (2017)
Anand Avati, Kenneth Jung, Stephanie Harman, Lance Downing, Andrew Y. Ng, Nigam H. Shah
Improving palliative care with deep learning. BIBM (2017)
Jianying Hu, Nigam H. Shah, Bradley A. Malin, Patrick B. Ryan, Anil Jain
Big Data for Healthcare and Life Sciences: Learning Useful Insights from Imperfect Data. AMIA (2016)
Alejandro Schuler, Vincent X. Liu, Joe Wan, Alison Callahan, Madeleine Udell, David E. Stark, Nigam H. Shah
Discovering Patient Phenotypes Using Generalized Low Rank Models. PSB (2016)
Alison Callahan, Saminda Abeyruwan, Hassan Al-Ali, Kunie Sakurai, Adam R. Ferguson, Phillip G. Popovich, Nigam H. Shah, Ubbo Visser, John L. Bixby, Vance P. Lemmon
RegenBase: a knowledge base of spinal cord injury biology for translational research. Database J. Biol. Databases Curation 2016 (2016)
Vibhu Agarwal, Tanya Podchiyska, Juan M. Banda, Veena Goel, Tiffany I. Leung, Evan P. Minty, Timothy E. Sweeney, Elsie Gyang, Nigam H. Shah
Learning statistical models of phenotypes using noisy labeled training data. J. Am. Medical Informatics Assoc. 23 (6) (2016)
Rainer Winnenburg, Nigam H. Shah
Generalized enrichment analysis improves the detection of adverse drug events from the biomedical literature. BMC Bioinform. 17 (2016)
Jon D. Duke, Nigam H. Shah, George Hripcsak, Patrick B. Ryan
Ensuring Reproducibility in Observational Research: Building and Sharing Knowledge Resources in the OHDSI Network. AMIA (2016)
Juan M. Banda, Tobias Kuhn, Nigam H. Shah, Michel Dumontier
Provenance-Centered Dataset of Drug-Drug Interactions. ISWC (2) (2015)
Larisa N. Soldatova, Nigel Collier, Anika Oellrich, Tudor Groza, Karin Verspoor, Philippe Rocca-Serra, Michel Dumontier, Nigam H. Shah
Special issue on bio-ontologies and phenotypes. J. Biomed. Semant. 6 (2015)
Olivier C. Curé, Henri Maurer, Nigam H. Shah, Paea LePendu
A formal concept analysis and semantic query expansion cooperation to refine health outcomes of interest. BMC Medical Informatics Decis. Mak. 15 (S-1) (2015)
Kenneth Jung, Nigam H. Shah
Implications of non-stationarity on predictive modeling using EHRs. J. Biomed. Informatics 58 (2015)
George Hripcsak, Jon D. Duke, Nigam H. Shah, Christian G. Reich, Vojtech Huser, Martijn J. Schuemie, Marc A. Suchard, Rae Woong Park, Ian Chi Kei Wong, Peter R. Rijnbeek, Johan van der Lei, Nicole Pratt, G. Niklas Norén, Yu-Chuan Li, Paul E. Stang, David Madigan, Patrick B. Ryan
Observational Health Data Sciences and Informatics (OHDSI): Opportunities for Observational Researchers. MedInfo (2015)
Guan Wang, Kenneth Jung, Rainer Winnenburg, Nigam H. Shah
A method for systematic discovery of adverse drug events from clinical notes. J. Am. Medical Informatics Assoc. 22 (6) (2015)
David J. Odgers, Rave Harpaz, Alison Callahan, Gregor Stiglic, Nigam H. Shah
Analyzing Search Behavior of Healthcare Professionals for Drug Safety Surveillance. Pacific Symposium on Biocomputing (2015)
Juan M. Banda, Tobias Kuhn, Nigam H. Shah, Michel Dumontier
Provenance-Centered Dataset of Drug-Drug Interactions. CoRR (2015)
Kenneth Jung, Paea LePendu, Srinivasan Iyer, Anna Bauer-Mehren, Bethany Percha, Nigam H. Shah
Functional evaluation of out-of-the-box text-mining tools for data-mining tasks. J. Am. Medical Informatics Assoc. 22 (1) (2015)
Sandy Huang, Paea LePendu, Srinivasan Iyer, Ming Tai-Seale, David Carrell, Nigam H. Shah
Toward personalizing treatment for depression: predicting diagnosis and severity. J. Am. Medical Informatics Assoc. 21 (6) (2014)
Larisa N. Soldatova, Philippe Rocca-Serra, Michel Dumontier, Nigam H. Shah
Selected papers from the 16th Annual Bio-Ontologies Special Interest Group Meeting. J. Biomed. Semant. 5 (S-1) (2014)
Srinivasan Iyer, Rave Harpaz, Paea LePendu, Anna Bauer-Mehren, Nigam H. Shah
Mining clinical text for signals of adverse drug-drug interactions. J. Am. Medical Informatics Assoc. 21 (2) (2014)
Ryen W. White, Nicholas P. Tatonetti, Nigam H. Shah, Russ B. Altman, Eric Horvitz
Web-scale pharmacovigilance: listening to signals from the crowd. J. Am. Medical Informatics Assoc. 20 (3) (2013)
Rave Harpaz, Santiago Vilar, William DuMouchel, Hojjat Salmasian, Krystl Haerian, Nigam H. Shah, Herbert S. Chase, Carol Friedman
Combing signals from spontaneous reports and electronic health records for detection of adverse drug reactions. J. Am. Medical Informatics Assoc. 20 (3) (2013)
Larisa N. Soldatova, Susanna-Assunta Sansone, Michel Dumontier, Nigam H. Shah
Selected papers from the 15th Annual Bio-Ontologies Special Interest Group Meeting. J. Biomed. Semant. 4 (S-1) (2013)
Rave Harpaz, William DuMouchel, Paea LePendu, Nigam H. Shah
Empirical bayes model to combine signals of adverse drug reactions. KDD (2013)
Tobias Wittkop, Emily TerAvest, Uday S. Evani, K. Mathew Fleisch, Ari E. Berman, Corey Powell, Nigam H. Shah, Sean D. Mooney
STOP using just GO: a multi-ontology hypothesis generation tool for high throughput experimentation. BMC Bioinform. 14 (2013)
Mark A. Musen, Natalya Fridman Noy, Nigam H. Shah, Patricia L. Whetzel, Christopher G. Chute, Margaret-Anne D. Storey, Barry Smith
The National Center for Biomedical Ontology. J. Am. Medical Informatics Assoc. 19 (2) (2012)
Yi Liu, Adrien Coulet, Paea LePendu, Nigam H. Shah
Using ontology-based annotation to profile disease research. J. Am. Medical Informatics Assoc. 19 (e1) (2012)
Larisa N. Soldatova, Susanna-Assunta Sansone, Michel Dumontier, Nigam H. Shah
Selected papers from the 14th Annual Bio-Ontologies Special Interest Group Meeting. J. Biomed. Semant. 3 (S-1) (2012)
Udo Hahn, Kevin Bretonnel Cohen, Yael Garten, Nigam H. Shah
Mining the pharmacogenomics literature - a survey of the state of the art. Briefings Bioinform. 13 (4) (2012)
Nigam H. Shah, Tyler Cole, Mark A. Musen
Chapter 9: Analyses Using Disease Ontologies. PLoS Comput. Biol. 8 (12) (2012)
Nigam H. Shah, Jessica D. Tenenbaum
The coming age of data-driven medicine: translational bioinformatics' next frontier. J. Am. Medical Informatics Assoc. 19 (e1) (2012)

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Publication Activity (10 Years)

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Nigam H. Shah