Randall C. Wetzel

25 papers A* 2B 1Misc 4Journal 15Unranked 3

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	A novel application of spectrograms with machine learning can detect patient ventilator dyssynchrony. Biomed. Signal Process. Control. Ishmael Obeso, Benjamin Yoon, David R. Ledbetter, Melissa Aczon, Eugene Laksana, Alice X. Zhou, R. Andrew Eckberg, Keith Mertan, Robinder G. Khemani, Randall C. Wetzel
2023	J	`jnl`	Narrowing the gap: expected versus deployment performance. J. Am. Medical Informatics Assoc. Alice X. Zhou, Melissa D. Aczon, Eugene Laksana, David R. Ledbetter, Randall C. Wetzel
2021	J	`jnl`	Improving Recurrent Neural Network Responsiveness to Acute Clinical Events. IEEE Access David R. Ledbetter, Eugene Laksana, Melissa Aczon, Randall C. Wetzel
2021	J	`jnl`	Interpreting a recurrent neural network's predictions of ICU mortality risk. J. Biomed. Informatics Long Van Ho, Melissa Aczon, David R. Ledbetter, Randall C. Wetzel
2021	J	`jnl`	Predicting High-Flow Nasal Cannula Failure in an ICU Using a Recurrent Neural Network with Transfer Learning and Input Data Perseveration: A Retrospective Analysis. CoRR George A. Pappy, Melissa D. Aczon, Randall C. Wetzel, David R. Ledbetter
2020	J	`jnl`	Improving Recurrent Neural Network Responsiveness to Acute Clinical Events. CoRR David R. Ledbetter, Eugene Laksana, Melissa Aczon, Randall C. Wetzel
2020	J	`jnl`	The impact of extraneous features on the performance of recurrent neural network models in clinical tasks. J. Biomed. Informatics Eugene Laksana, Melissa Aczon, Long Van Ho, Cameron Carlin, David R. Ledbetter, Randall C. Wetzel
2019	J	`jnl`	Interpreting a Recurrent Neural Network Model for ICU Mortality Using Learned Binary Masks. CoRR Long Van Ho, Melissa D. Aczon, David R. Ledbetter, Randall C. Wetzel
2019	J	`jnl`	Predicting Individual Responses to Vasoactive Medications in Children with Septic Shock. CoRR Nicole Fronda, Jessica Asencio, Cameron Carlin, David R. Ledbetter, Melissa Aczon, Randall C. Wetzel, Barry Markovitz
2019	J	`jnl`	The Impact of Extraneous Variables on the Performance of Recurrent Neural Network Models in Clinical Tasks. CoRR Eugene Laksana, Melissa Aczon, Long Van Ho, Cameron Carlin, David R. Ledbetter, Randall C. Wetzel
2018	Misc	`conf`	Heat Map, a Visual Tool for Comparative Analytics. AMIA Jamie C. Palumbo, Randall C. Wetzel, Gerardo Soto-Campos
2018	J	`jnl`	Predicting individual physiologically acceptable states at discharge from a pediatric intensive care unit. J. Am. Medical Informatics Assoc. Cameron Carlin, Long Van Ho, David R. Ledbetter, Melissa D. Aczon, Randall C. Wetzel
2017	J	`jnl`	Dynamic Mortality Risk Predictions in Pediatric Critical Care Using Recurrent Neural Networks. CoRR Melissa Aczon, David R. Ledbetter, Long Van Ho, Alec M. Gunny, Alysia Flynn, Jon Williams, Randall C. Wetzel
2017	—	`conf`	Marked Point Process for Severity of Illness Assessment. MLHC Kazi T. Islam, Christian R. Shelton, Juan I. Casse, Randall C. Wetzel
2017	J	`jnl`	Predicting Individual Physiologically Acceptable States for Discharge from a Pediatric Intensive Care Unit. CoRR Cameron Carlin, Long Van Ho, David R. Ledbetter, Melissa Aczon, Randall C. Wetzel
2017	Misc	`conf`	The Dependence of Machine Learning on Electronic Medical Record Quality. AMIA Long Van Ho, David R. Ledbetter, Melissa D. Aczon, Randall C. Wetzel
2016	Misc	`conf`	DRTED: Deep learning Recommendation of Treatment from Electronic Data. AMIA Melissa Aczon, David R. Ledbetter, Long Van Ho, Alec M. Gunny, Randall C. Wetzel
2016	—	`conf`	Directly Modeling Missing Data in Sequences with RNNs: Improved Classification of Clinical Time Series. MLHC Zachary C. Lipton, David C. Kale, Randall C. Wetzel
2016	J	`jnl`	Directly Modeling Missing Data in Sequences with RNNs: Improved Classification of Clinical Time Series. CoRR Zachary Chase Lipton, David C. Kale, Randall C. Wetzel
2016	A*	`conf`	Learning to Diagnose with LSTM Recurrent Neural Networks. ICLR (Poster) Zachary Chase Lipton, David C. Kale, Charles Elkan, Randall C. Wetzel
2015	Misc	`conf`	Causal Phenotype Discovery via Deep Networks. AMIA David C. Kale, Zhengping Che, Mohammad Taha Bahadori, Wenzhe Li, Yan Liu, Randall C. Wetzel
2015	J	`jnl`	Phenotyping of Clinical Time Series with LSTM Recurrent Neural Networks. CoRR Zachary Chase Lipton, David C. Kale, Randall C. Wetzel
2014	A*	`conf`	An Examination of Multivariate Time Series Hashing with Applications to Health Care. ICDM David C. Kale, Dian Gong, Zhengping Che, Yan Liu, Gérard G. Medioni, Randall C. Wetzel, Patrick Ross
2012	—	`conf`	Unsupervised pattern discovery in electronic health care data using probabilistic clustering models. IHI Benjamin M. Marlin, David C. Kale, Robinder G. Khemani, Randall C. Wetzel
2011	B	`conf`	An informatics architecture for the Virtual Pediatric Intensive Care Unit. CBMS Daniel J. Crichton, Chris A. Mattmann, Andrew F. Hart, David C. Kale, Robinder G. Khemani, Patrick Ross, Sarah Rubin, Paul Veeravatanayothin, Amy Braverman, Cameron Goodale, Randall C. Wetzel

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.