Neural Language Correction with Character-Based Attention. - Ziang Xie; Anand Avati; Naveen Arivazhagan; Dan Jurafsky; Andrew Y. Ng (CoRR, 2016)

Capturing Heterogeneity in Complex Chronic Illness: Building a Model for Systemic Lupus Erythematosus (SLE) with "Noisy Labeling" of Data. - Sara G. Murray; Anand Avati; Gabriela Schmajuk; Jinoos Yazdany (AMIA, 2018)

Countdown Regression: Sharp and Calibrated Survival Predictions. - Anand Avati; Tony Duan; Kenneth Jung; Nigam H. Shah; Andrew Y. Ng (CoRR, 2018)

Predicting Inpatient Discharge Prioritization With Electronic Health Records. - Anand Avati; Stephen Pfohl; Chris Lin; Thao Nguyen; Meng Zhang; Philip Hwang; Jessica Wetstone; Kenneth Jung; Andrew Y. Ng; Nigam H. Shah (CoRR, 2018)

Improving palliative care with deep learning. - Anand Avati; Kenneth Jung; Stephanie Harman; Lance Downing; Andrew Y. Ng; Nigam H. Shah (BMC Medical Informatics Decis. Mak., 2018)

Ambulatory Atrial Fibrillation Monitoring Using Wearable Photoplethysmography with Deep Learning. - Yichen Shen 003; Maxime Voisin; Alireza Aliamiri; Anand Avati; Awni Y. Hannun; Andrew Y. Ng (KDD, 2019)

Countdown Regression: Sharp and Calibrated Survival Predictions. - Anand Avati; Tony Duan; Sharon Zhou; Kenneth Jung; Nigam H. Shah; Andrew Y. Ng (UAI, 2019)

NGBoost: Natural Gradient Boosting for Probabilistic Prediction. - Tony Duan; Anand Avati; Daisy Yi Ding; Sanjay Basu; Andrew Y. Ng; Alejandro Schuler (CoRR, 2019)

Automated and flexible identification of complex disease: building a model for systemic lupus erythematosus using noisy labeling. - Sara G. Murray; Anand Avati; Gabriela Schmajuk; Jinoos Yazdany (J. Am. Medical Informatics Assoc., 2019)

NGBoost: Natural Gradient Boosting for Probabilistic Prediction. - Tony Duan; Anand Avati; Daisy Yi Ding; Khanh K. Thai; Sanjay Basu; Andrew Y. Ng; Alejandro Schuler (ICML, 2020)

BEDS-Bench: Behavior of EHR-models under Distributional Shift-A Benchmark. - Anand Avati; Martin Seneviratne; Emily Xue; Zhen Xu 006; Balaji Lakshminarayanan; Andrew M. Dai (CoRR, 2021)

A framework for making predictive models useful in practice. - Kenneth Jung; Sehj Kashyap; Anand Avati; Stephanie Harman; Heather Shaw; Ron C. Li; Margaret Smith; Kenny Shum; Jacob Javitz; Yohan Vetteth; Tina Seto; Steven C. Bagley; et al. (J. Am. Medical Informatics Assoc., 2021)

Improving hospital readmission prediction using individualized utility analysis. - Michael Ko; Emma Chen; Ashwin Agrawal; Pranav Rajpurkar; Anand Avati; Andrew Yan-Tak Ng; Sanjay Basu; Nigam H. Shah (J. Biomed. Informatics, 2021)

AI-enabled palliative care : from algorithms to clinical deployment. - Anand Avati (2022)