Nemati, Shamim

An interpretable machine learning model for accurate prediction of sepsis in the ICU

Nemati, S., Holder, A., Razmi, F., Stanley, M. D., Clifford, G. D., & Buchman, T. G. (2018) · Critical Care Medicine

Sepsis Diagnosis and TreatmentMachine Learning in Healthcare

Cited by 832

Early Prediction of Sepsis From Clinical Data: The PhysioNet/Computing in Cardiology Challenge 2019

Reyna, M. A., Josef, C. S., Jeter, R., Shashikumar, S. P., Westover, M. B., Nemati, S., Clifford, G. D., & Sharma, A. (2020) · Critical Care Medicine

Sepsis Diagnosis and TreatmentMachine Learning in Healthcare

Cited by 383

Quantifying the ventilatory control contribution to sleep apnoea using polysomnography

Terrill, P. I., Edwards, B. A., Nemati, S., Butler, J. P., Owens, R. L., Eckert, D. J., White, D. P., Malhotra, A., Wellman, A., & Sands, S. A. (2015) · European Respiratory Journal

Obstructive Sleep Apnea ResearchNeuroscience of respiration and sleep

Cited by 289

A simplified method for determining phenotypic traits in patients with obstructive sleep apnea

Wellman, A., Edwards, B. A., Sands, S. A., Owens, R. L., Nemati, S., Butler, J., Passaglia, C. L., Jackson, A. C., Malhotra, A., & White, D. P. (2013) · Journal of Applied Physiology

Obstructive Sleep Apnea ResearchNeuroscience of respiration and sleep

Cited by 222

Optimal medication dosing from suboptimal clinical examples: a deep reinforcement learning approach

Nemati, S., Ghassemi, M. M., & Clifford, G. D. (2016) · 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 195

Impact of a deep learning sepsis prediction model on quality of care and survival

Boussina, A., Shashikumar, S. P., Malhotra, A., Owens, R. L., El-Kareh, R., Longhurst, C. A., Quintero, K., Donahue, A., Chan, T. C., Nemati, S., et al. (2024) · npj Digital Medicine

Sepsis Diagnosis and TreatmentMachine Learning in Healthcare

Cited by 170

Early sepsis detection in critical care patients using multiscale blood pressure and heart rate dynamics

Shashikumar, S. P., Stanley, M. D., Sadiq, I., Li, Q., Holder, A., Clifford, G. D., & Nemati, S. (2017) · Journal of Electrocardiology

Sepsis Diagnosis and TreatmentHeart Rate Variability and Autonomic Control

Cited by 167

Classifying major depressive disorder and response to deep brain stimulation over time by analyzing facial expressions

Jiang, Z., Harati, S., Crowell, A., Mayberg, H. S., Nemati, S., & Clifford, G. D. (2021) · IEEE Transactions on Biomedical Engineering

Emotion and Mood RecognitionFace recognition and analysis

Cited by 60

Respiration and heart rate complexity: effects of age and gender assessed by band-limited transfer entropy

Nemati, S., Edwards, B. A., Lee, J., Pittman-Polletta, B., Butler, J. P., & Malhotra, A. (2013) · Respiratory Physiology & Neurobiology

Heart Rate Variability and Autonomic ControlNon-Invasive Vital Sign Monitoring

Cited by 58

Bringing the Promise of Artificial Intelligence to Critical Care: What the Experience With Sepsis Analytics Can Teach Us

Wardi, G., Owens, R., Josef, C., Malhotra, A., Longhurst, C., & Nemati, S. (2023) · Critical Care Medicine

Sepsis Diagnosis and TreatmentMachine Learning in Healthcare

Cited by 35

Assessing Barriers to Implementation of Machine Learning and Artificial Intelligence–Based Tools in Critical Care: Web-Based Survey Study

Mlodzinski, E., Wardi, G., Viglione, C., Nemati, S., Crotty Alexander, L., & Malhotra, A. (2023) · JMIR Perioperative Medicine

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 28