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Matthew A Levin

Explore the profile of Matthew A Levin including associated specialties, affiliations and a list of published articles. Areas
Snapshot
Articles 91
Citations 2681
Followers 0
Related Specialties
Anesthesiology
Cardiology & Vascular Diseases
General Medicine
Top 10 Co-Authors
Benjamin S Glicksberg
David L Reich
Hung-Mo Lin
Robert Freeman
Girish N Nadkarni
Prem Timsina
Alexander W Charney
Arash Kia
Eyal Klang
Shan Zhao
Published In
Anesth Analg
J Cardiothorac Vasc Anesth
medRxiv
Anesthesiology
J Med Syst
Affiliations
Soon will be listed here.
Recent Articles
1.
Electronic-Medical-Record-Driven Machine Learning Predictive Model for Hospital-Acquired Pressure Injuries: Development and External Validation
Nguyen K, Patel D, Edalati M, Sevillano M, Timsina P, Freeman R, et al.
J Clin Med . 2025 Feb; 14(4). PMID: 40004706
Hospital-acquired pressure injuries (HAPIs) affect approximately 2.5 million patients annually in the United States, leading to increased morbidity and healthcare costs. Current rule-based screening tools, such as the Braden Scale,...
2.
Perioperative Near Infrared Spectroscopy Measurements of Cerebral Regional Oxygen Desaturations Are Not Associated With Delirium After Cardiac Surgery
Kahn R, Egorova N, Ouyang Y, Huang J, Levin M, Hofer I, et al.
J Cardiothorac Vasc Anesth . 2025 Feb; PMID: 40000288
Objective: Postoperative delirium remains a common complication after cardiac surgery in high-risk patients and has been associated with prolonged intensive care unit length of stay, overall morbidity, and mortality. It...
3.
Comparison of Perioperative Outcomes for Transfusion of Hemoconcentrated Bypass Versus Cell Saver Blood in Cardiac Surgical Patients
Bhatt H, Hu Y, Lin H, Egorova N, Ouyang Y, Levin M
J Cardiothorac Vasc Anesth . 2025 Feb; PMID: 39984367
Objective: Hemoconcentration and cell saver use are blood conservation techniques that are often used in cardiac surgery to salvage the patient's own blood to reduce autologous transfusion. The purpose of...
4.
Association of Intraoperative Occult Hypoxemia With 30-Day and 1-Year Mortality
Stannard B, Burnett G, Wax D, Egorova N, Ouyang Y, Pyram-Vincent C, et al.
Anesth Analg . 2025 Feb; PMID: 39903680
Background: Despite the widespread use of pulse oximetry for intraoperative estimation of arterial oxygen saturation, there is growing evidence that certain patient populations may be vulnerable to inaccurate pulse oximetry...
5.
Traditional Machine Learning, Deep Learning, and BERT (Large Language Model) Approaches for Predicting Hospitalizations From Nurse Triage Notes: Comparative Evaluation of Resource Management
Patel D, Timsina P, Gorenstein L, Glicksberg B, Raut G, Cheetirala S, et al.
JMIR AI . 2024 Aug; 3:e52190. PMID: 39190905
Background: Predicting hospitalization from nurse triage notes has the potential to augment care. However, there needs to be careful considerations for which models to choose for this goal. Specifically, health...
6.
Development and Validation of a Deep Learning Classifier Using Chest Radiographs to Predict Extubation Success in Patients Undergoing Invasive Mechanical Ventilation
Tandon P, Nguyen K, Edalati M, Parchure P, Raut G, Reich D, et al.
Bioengineering (Basel) . 2024 Jun; 11(6). PMID: 38927862
The decision to extubate patients on invasive mechanical ventilation is critical; however, clinician performance in identifying patients to liberate from the ventilator is poor. Machine Learning-based predictors using tabular data...
7.
Assessing calibration and bias of a deployed machine learning malnutrition prediction model within a large healthcare system
Liou L, Scott E, Parchure P, Ouyang Y, Egorova N, Freeman R, et al.
NPJ Digit Med . 2024 Jun; 7(1):149. PMID: 38844546
Malnutrition is a frequently underdiagnosed condition leading to increased morbidity, mortality, and healthcare costs. The Mount Sinai Health System (MSHS) deployed a machine learning model (MUST-Plus) to detect malnutrition upon...
8.
Real-Time Machine Learning Alerts to Prevent Escalation of Care: A Nonrandomized Clustered Pragmatic Clinical Trial
Levin M, Kia A, Timsina P, Cheng F, Nguyen K, Kohli-Seth R, et al.
Crit Care Med . 2024 Feb; 52(7):1007-1020. PMID: 38380992
Objectives: Machine learning algorithms can outperform older methods in predicting clinical deterioration, but rigorous prospective data on their real-world efficacy are limited. We hypothesized that real-time machine learning generated alerts...
9.
A Hybrid Decision Tree and Deep Learning Approach Combining Medical Imaging and Electronic Medical Records to Predict Intubation Among Hospitalized Patients With COVID-19: Algorithm Development and Validation
Nguyen K, Tandon P, Ghanavati S, Cheetirala S, Timsina P, Freeman R, et al.
JMIR Form Res . 2023 Oct; 7:e46905. PMID: 37883177
Background: Early prediction of the need for invasive mechanical ventilation (IMV) in patients hospitalized with COVID-19 symptoms can help in the allocation of resources appropriately and improve patient outcomes by...
10.
Machine learning using institution-specific multi-modal electronic health records improves mortality risk prediction for cardiac surgery patients
Weiss A, Yadaw A, Meretzky D, Levin M, Adams D, McCardle K, et al.
JTCVS Open . 2023 Jul; 14:214-251. PMID: 37425442
Background: The Society of Thoracic Surgeons risk scores are widely used to assess risk of morbidity and mortality in specific cardiac surgeries but may not perform optimally in all patients....