Word Cloud created from abstracts of my accepted papers (wordle.net/)

2024

  1. Non-invasive pulse arrival time is associated with cardiac index in pediatric heart transplant patients with normal ejection fraction. Kwon, S.; Weinerman, B.; Nametz, D.; Megjhani, M.; Lee, I.; Habib, A.; Barry, O.; Park, S. Physiological Measurement, 45(7), 07NT01, 2024.

2023

  1. Suboptimal Cerebral Perfusion is Associated with Ischemia After Intracerebral Hemorrhage. Ridha, M.; Megjhani, M.; Nametz, D.; Kwon, S.B.; Velazquez, A.; Ghoshal, S.; Agarwal, S.; Claassen, J.; Roh, D.J.; Connolly Jr, E.S.; Park, S. Neurocritical Care, 2023, pp. 1–10.
  2. Heart rate and heart rate variability as a prognosticating feature for functional outcome after cardiac arrest: A scoping review. Kwon, S.B.; Megjhani, M.; Nametz, D.; Agarwal, S.; Park, S. Resuscitation Plus, 15, 100450, 2023.
  3. Automatic identification of intracranial pressure waveform during external ventricular drainage clamping: segmentation via wavelet analysis. Megjhani, M.; Terilli, K.; Kwon, S.B.; Nametz, D.; Weinerman, B.; Velazquez, A.; Ghoshal, S.; Roh, D.; Agarwal, S.; Connolly, E.S.; Claassen, J. Physiological Measurement, 44(6), 064002, 2023.
  4. A Deep Learning Framework for Deriving Noninvasive Intracranial Pressure Waveforms from Transcranial Doppler. Megjhani, M.; Terilli, K.; Weinerman, B.; Nametz, D.; Kwon, S.B.; Velazquez, A.; Ghoshal, S.; Roh, D.J.; Agarwal, S.; Connolly Jr, E.S.; Claassen, J. Annals of Neurology, 94(1), 196–202, 2023.
  5. The oxygen reactivity index indicates disturbed local perfusion regulation after aneurysmal subarachnoid hemorrhage: an observational cohort study. Kastenholz, N.; Megjhani, M.; Conzen-Dilger, C.; Albanna, W.; Veldeman, M.; Nametz, D.; Kwon, S.B.; Schulze-Steinen, H.; Ridwan, H.; Clusmann, H.; Schubert, G.A. Critical Care, 27(1), 235, 2023.
  6. Mathematical model of SARS-CoV-2 immunity predicts Paxlovid rebound. Ranard, B.L.; Vodovotz, Y.; Asgari, S.; Megjhani, M.; Chow, C.C.; Park, S. Journal of Critical Care, 74, 154210, 2023.
  7. A Deep Learning Framework for Deriving Non‑Invasive Intracranial Pressure Waveforms from Transcranial Doppler. Megjhani, M.; Terilli, K.; Weinerman, B.; Nametz, D.; Kwon, S.B.; Velazquez, A.; Ghoshal, S.; Roh, D.J.; Agarwal, S.; Connolly Jr, E.S.; Claassen, J. Annals of Neurology, 2023.
  8. Classification of Level of Consciousness in a Neurological ICU Using Physiological Data. Gomez, L.A.; Shen, Q.; Doyle, K.; Vrosgou, A.; Velazquez, A.; Megjhani, M.; Ghoshal, S.; Roh, D.; Agarwal, S.; Park, S.; Claassen, J. Neurocritical Care, 38(1), 118–128, Feb 2023.
  9. Optimal cerebral perfusion pressure and brain tissue oxygen in aneurysmal subarachnoid hemorrhage. Megjhani, M.; Weiss, M.; Ford, J.; Terilli, K.; Kastenholz, N.; Nametz, D.; Kwon, S.B.; Velazquez, A.; Agarwal, S.; Roh, D.J.; Conzen-Dilger, C. Stroke, 54(1), 189–197, Jan 2023.

2022

  1. Heart rate variability and adrenal size provide clues to sudden cardiac death in hospitalized COVID‑19 patients. Ranard, B.; Megjhani, M.; Terilli, K.; Yarmohammadi, H.; Ausiello, J.; Park, S. Journal of Critical Care, Oct 2022.
  2. Intraarterial nimodipine versus induced hypertension for delayed cerebral ischemia: a modified treatment protocol. Weiss, M.; Albanna, W.; Conzen‑Dilger, C.; Kastenholz, N.; Seyfried, K.; Ridwan, H.; Wiesmann, M.; Veldeman, M.; Schmidt, T.P.; Megjhani, M.; Schulze‑Steinen, H.; Schubert, G.A. Stroke, 53(8), 2607–2616, 2022.
  3. Predicting Shunt Dependency from the Effect of Cerebrospinal Fluid Drainage on Ventricular Size. Rubinos, C.; Kwon, S.B.; Megjhani, M.; Terilli, K.; Wong, B.; Cespedes, L.; Ford, J.; Reyes, R.; Kirsch, H.; Alkhachroum, A.; Velazquez, A.; Roh, D.; Agarwal, S.; Connolly, E.; Boehme, A.; Claassen, J.; Park, S. Neurocritical Care, 2022.
  4. Vector Angle Analysis of Multimodal Neuromonitoring Data for Continuous Prediction of Delayed Cerebral Ischemia. Megjhani, M.; Weiss, M.; Kwon, S.B.; Ford, J.; Nametz, D.; Kastenholz, N.; ...; Park, S. Neurocritical Care, 2022, pp. 1–7.
  5. Optimal Cerebral Perfusion Pressure During Delayed Cerebral Ischemia After Aneurysmal Subarachnoid Hemorrhage. Weiss, M.; Albanna, W.; Conzen, C.; Megjhani, M.; Tas, J.; Seyfried, K.; Schubert, G.A. Critical Care Medicine, 50(2), 183–191, 2022.

2021

  1. Dynamic Intracranial Pressure Waveform Morphology Predicts Ventriculitis. Megjhani, M.; Terilli, K.; Kalaspudi, L.; Chen, J.; Carlson, J.; Miller, S.; Badjatia, N.; Hu, P.; Velazquez, A.; Roh, D.; Agarwal, A.; Claassen, J.; Connolly, E.S.; Hu, X.; Morris, N.; Park, S. Neurocritical Care, 2021, pp. 1–8.
  2. Identification of endotypes of hospitalized COVID‑19 patients. Ranard, B.; Megjhani, M.; Terilli, K.; Doyle, K.; Claassen, J.; Pinsky, M.; Clermont, G.; Vodovotz, Y.; Asgari, S.; Park, S. Frontiers in Medicine, 8, 2021.
  3. Dynamic Detection of Delayed Cerebral Ischemia: A Study in Three Centers. Megjhani, M.; Terilli, K.*; Weiss, M.; Savarraj, S.; Chen, L.H.; Alkhachroum, A.; Roh, D.; Agarwal, S.; Connolly, E.S.; Velazquez, A.; Boehme, A.; Claassen, J.; Choi, H.A.; Schubert, G.; Park, S. Stroke, 52(4), 1370–1379, 2021.

2020

  1. The Association Between Peri‑Hemorrhagic Metabolites and Cerebral Hemodynamics in Comatose Patients With Spontaneous Intracerebral Hemorrhage: An International Multicenter Pilot Study Analysis. Rasulo, F.; Piva, S.; Park, S.; Oddo, M.; Megjhani, M.; Cardim, D.; Matteotti, I.; Gandolfi, L.; Robba, G.; Taccone, F.S.; Latronico, N. Frontiers in Neurology, Sep 2020.
  2. Machine learning to predict delayed cerebral ischemia and outcomes in subarachnoid hemorrhage. Savarraj, J.; Hergenroeder, G.; Zhu, L.; Chang, T.; Park, S.; Megjhani, M.; Vahidy, F.; Zhao, Z.; Kitagawa, R.; Choi, H.A. Neurology, 2020.
  3. Harnessing Big Data in Neurocritical Care in the Era of Precision Medicine. Alkhachroum, A.*; Terilli, K.*; Megjhani, M.*; Park, S. Current Treatment Options in Neurology, 22(5), 2020.
  4. Surface Point Cloud Ultrasound with Transcranial Doppler: Coregistration of Surface Point Cloud Ultrasound with Magnetic Resonance Angiography for Improved Reproducibility, Visualization, and Navigation in Transcranial Doppler Ultrasound. Stember, J.N.; Terilli, K.L.; Perez, E.; Megjhani, M.; Cooper, C.A.; Jambawalikar, S.; Park, S. Journal of Digital Imaging, 2020, pp. 1–7.

2019

  1. Hyperemia in subarachnoid hemorrhage patients is associated with an increased risk of seizures. Alkhachroum, A.; Megjhani, M.; Terilli, K.; Rubinos, C.; Ford, J.; Wallace, B.; Roh, D.; Agarwal, S.; Connolly, E.; Boehme, A.; Claassen, J.; Park, S. Journal of Cerebral Blood Flow & Metabolism, 2019.
  2. Detection of Brain Activation in Unresponsive Patients with Acute Brain Injury. Claassen, J.; Doyle, K.; Matory, A.; Couch, C.; Burger, K.; Velazquez, A.; Okonkwo, J.; King, J.R.; Park, S.; Agarwal, S.; Roh, D.; Megjhani, M.; Eliseyev, A.; Connolly, E.; Rohaut, B. New England Journal of Medicine, 380, 2497–2505, 2019.
  3. Heart Rate Variability as a Biomarker of Neurocardiogenic Injury after Subarachnoid Hemorrhage. Megjhani, M.; Kaffashi, F.; Terilli, K.; Alkhachroum, A.; Esmaeili, B.; Doyle, K.; Murthy, S.; Velazquez, A.; Connolly, E.; Roh, D.; Agarwal, S.; Loparo, K.; Claassen, J.; Boehme, A.; Park, S. Neurocritical Care, 2019.
  4. Deep structural brain lesions associated with consciousness impairment early after hemorrhagic stroke. Rohaut, B.; Doyle, K.; Reynolds, A.; Igwe, K.; Couch, C.; Matory, A.; Rizvi, B.; Roh, D.; Velazquez, A.; Megjhani, M.; et al. Scientific Reports, 9(1), 4174, 2019.
  5. Use of Clustering to Investigate Changes in Intracranial Pressure Waveform Morphology in Patients with Ventriculitis. Megjhani, M.; Terilli, K.; Kaplan, A.; Wallace, B.K.; Alkhachroum, A.; Hu, X.; Park, S. Physiological Measurement, 40(1), 015002, Jan 2019.

2018

  1. An active learning framework for enhancing identification of non‑artifactual intracranial pressure waveforms. Megjhani, M.; Terilli, K.; Park, S.; et al. Physiological Measurement, Dec 2018.
  2. Predicting Delayed Cerebral Ischemia after Subarachnoid Hemorrhage Using High Frequency Physiological Data. Park, S.; Megjhani, M.; Claassen, J.; Elhadad, N. Journal of Clinical and Medical Computing, 2018.
  3. Incorporating High Frequency Physiologic Data Using Computational Dictionary Learning Improves Prediction of Delayed Cerebral Ischemia Compared to Existing Methods. Megjhani, M.; Terilli, K.; Claassen, J.; Elhadad, N.; Park, S. Frontiers in Neurology, Feb 2018.
  4. Deriving the PRx and CPPopt from 0.2‑Hz Data: Establishing Generalizability to Bedmaster Users. Megjhani, M.; Terilli, K.; Martin, A.; Velazquez, A.; Claassen, J.; Park, S. In: Heldt T. (ed.) Intracranial Pressure & Neuromonitoring XVI, Acta Neurochirurgica Supplement, vol 126. Springer, Cham, 2018.

2017

  1. Deployment of Mobile EEG Technology in an Art Museum Setting: Evaluation of Signal Quality and Usability. Cruz‑Garza, J.; Brantley, J.; Nakagome, S.; Kontson, K.; Megjhani, M.; Robleto, D.; Contreras‑Vidal, J.L. Frontiers in Human Neuroscience, Nov 2017.
  2. Morphological Constraint Spectral Unmixing of Biological Tissues Using Confocal Microscopy. Megjhani, M.; Roysam, B. Bioinformatics, 2017.
  3. Binge Alcohol Alters Exercise‑Driven Neuroplasticity. Barton, E.; Lu, Y.; Megjhani, M.; Maynard, M.; Kulkarni, P.; Roysam, B.; Leasure, J.L. Neuroscience, 343, Feb 2017.

2015

  1. Your Brain on Art: Emergent Cortical Dynamics During Aesthetic Experiences. Megjhani, M.*; Kontson, K.*; Cruz‑Garza, J.G.; Brantley, J.A.; Robleto, D.; Contreras‑Vidal, J.L. Frontiers in Human Neuroscience, Nov 2015.
  2. Population‑scale Three‑dimensional Reconstruction and Quantitative Profiling of Microglia Arbors. Megjhani, M.; Rey‑Villamizar, N.; Merouane, A.; Lu, Y.; Mukherjee, A.; Trett, K.; Chong, P.; Harris, C.; Shain, W.; Roysam, B. Bioinformatics, 31, 2190–2198, Feb 2015.
  3. Unsupervised Profiling of Microglial Arbor Morphologies and Distribution Using a Nonparametric Bayesian Approach. Xu, Y.; Megjhani, M.; Shain, W.; Roysam, B.; Han, Z. IEEE Journal of Selected Topics in Signal Processing, Jan 2015.

2014

  1. Large‑scale Automated Image Analysis for Computational Profiling of Brain Tissue Surrounding Implanted Neuroprosthetic Devices Using Python. Rey‑Villamizar, N.; Somasundar, V.; Megjhani, M.; Xu, Y.; Lu, Y.; Padmanabhan, R.; Trett, K.; Shain, W.; Roysam, B. Frontiers in Neuroinformatics, 8(39), Apr 2014.