


Dr. Leo Celi, MD
Dr. Leo Celi, MD is a critical care medicine specialist in Boston, MA and has over 30 years of experience in the medical field. He graduated from NORTHWEST SHOALS COMMUNITY COLLEGE-PHIL CAMPBELL in 1990. He is affiliated with Beth Israel Deaconess Medical Center.
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330 Brookline Ave Boston, MA 02215Make an Appointment
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Dr. Leo Celi, MD is a critical care medicine specialist in Boston, MA and has over 30 years of experience in the medical field. He graduated from NORTHWEST SHOALS COMMUNITY COLLEGE-PHIL CAMPBELL in 1990. He is affiliated with Beth Israel Deaconess Medical Center.Critical Care Medicine
*Healthgrades does not verify qualifications for medical specialties. Please verify your provider's specialty and qualifications directly with your provider and applicable medical board.
Northwest Shoals Community College-phil Campbell
Medical School, 1990
Healthgrades receives board action history for physicians and physician assistants. The information displayed here is sourced from independent information providers, such as state board websites, and may not be the most up-to-date information. Healthgrades makes no representations with respect to the accuracy of any information provided here and assumes no responsibility or liability for such information.
Learn more about medical license public record checkA novel Vascular Leak Index identifies sepsis patients with a higher risk for in-hospital death and fluid accumulation, 2022-04-11
Village mentoring and hive learning: The MIT Critical Data experience, 2021-06-10
Hyperdynamic left ventricular ejection fraction in the intensive care unit, 2015-08-07
A new tool for evaluating health equity in academic journals; the Diversity Factor, 2023-08-14
A translational perspective towards clinical AI fairness, 2023-09-14
Big data in healthcare: are we close to it? Big Dataem saude: estamos perto?, 2016-01-01
Conversation prior to resuscitation: The new CPR, 2015-12-29
Association of hypokalemia with an increased risk for medically treated arrhythmias, 2019-06-17
BRAX, Brazilian labeled chest x-ray dataset, 2022-08-10
Applying Machine Learning to Continuously Monitored Physiological Data, 2018-11-11
The reproducibility crisis in the age of digital medicine, 2019-01-29
Sources of bias in artificial intelligence that perpetuate healthcare disparities-A global review, 2022-03-31
A systematic review of federated learning applications for biomedical data, 2022-05-19
Fairness and generalizability of OCT normative databases: a comparative analysis, 2023-08-21
Proton Pump Inhibitors are not associated with Acute Kidney Injury in Critical Illness, 2016-09-12
Datathons and Software to Promote Reproducible Research, 2016-08-24
The potential use of non-fungible tokens (NFTs) in healthcare and medical research, 2023-07-27
Proton-pump inhibitor use is associated with low serum magnesium concentrations, 2013-01-16
One-year mortality after recovery from critical illness: A retrospective cohort study, 2018-05-11
A comparative analysis of sepsis identification methods in an electronic database, 2017-12-08
Patient-specific COVID-19 resource utilization prediction using fusion AI model, 2021-06-03
Disrupting Electronic Health Records Systems: The Next Generation, 2015-10-23
Unsupervised learning for county-level typological classification for COVID-19 research, 2020-08-30
Author Correction: MIMIC-IV, a freely accessible electronic health record dataset, 2023-01-16
The Global Open Source Severity of Illness Score (GOSSIS), 2022-03-25
What do medical students actually need to know about artificial intelligence?, 2020-06-19
The advent of medical artificial intelligence: lessons from the Japanese approach, 2020-05-18
Equity should be fundamental to the emergence of innovation, 2023-04-10
Increased incidence of diuretic use in critically ill obese patients, 2015-02-07
Author Correction: The reproducibility crisis in the age of digital medicine, 2019-03-19
MIMIC-IV, a freely accessible electronic health record dataset, 2023-01-03
Digital literacy as a new determinant of health: A scoping review, 2023-10-12
Addressing the "elephant in the room” of AI clinical decision support through organisation-level regulation, 2022-09-15
Improving community health-care screenings with smartphone-based AI technologies, 2022-05-23
Preparing a New Generation of Clinicians for the Era of Big Data, 2015-01-16
MIMIC-III, a freely accessible critical care database, 2016-05-24
ChatGPT passing USMLE shines a spotlight on the flaws of medical education, 2023-02-09
The promise of digital healthcare technologies, 2023-09-26
Crowdsourcing Knowledge Discovery and Innovations in Medicine, 2014-09-19
An evaluation of the influence of body mass index on severity scoring., 2018-10-08
Dynamic Clinical Data Mining: Search Engine-Based Decision Support, 2014-06-23
High resolution data modifies intensive care unit dialysis outcome predictions as compared with low resolution administrative data set, 2022-10-11
Accelerating ophthalmic AI research: the role of an open access data repository, 2021-04-14
Artificial intelligence for telemedicine diabetic retinopathy screening: a review, 2023-09-21
Obesity, Acute Kidney Injury, and Mortality in Critical Illness, 2015-09-04
A data-driven approach to optimized medication dosing: a focus on heparin, 2014-08-05
Physician satisfaction with a multi-platform digital scheduling system, 2017-03-22
Effectiveness of automated alerting system compared to usual care for the management of sepsis, 2022-07-19
A distributed approach to the regulation of clinical AI, 2022-05-26
Clinical Note Creation, Binning, and Artificial Intelligence, 2017-08-03
Racial and Geographic Disparities in Inter-Hospital Intensive Care Unit Transfers, 2017-09-15
Trends in Severity of Illness on ICU Admission and Mortality among the Elderly, 2014-04-03
Performance of intensive care unit severity scoring systems across different ethnicities, 2021-01-20
Author Correction: MIMIC-IV, a freely accessible electronic health record dataset, 2023-04-18
Focus on Asthma
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- Recipient of 10
hospital awardsView all patient feedbackHow patients felt about the care they received at this hospital.
88%Patients said they were given information about recovering at home4% higher than the national average
78%Patients said that nurses always listened to them and explained things well3% higher than the national average
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