A. Kia

发表

Anticoagulation, Bleeding, Mortality, and Pathology in Hospitalized Patients With COVID-19

Benjamin S. Glicksberg, V. Fuster, C. Cordon-Cardo, 2020, Journal of the American College of Cardiology.

Anticoagulation, Bleeding, Mortality, and Pathology in Hospitalized Patients With COVID-19

Benjamin S. Glicksberg, V. Fuster, C. Cordon-Cardo, 2020, Journal of the American College of Cardiology.

MUST-Plus: A Machine Learning Classifier That Improves Malnutrition Screening in Acute Care Facilities

M. Mazumdar, D. Reich, J. Mechanick, 2020, Journal of the American College of Nutrition.

MEWS++: Enhancing the Prediction of Clinical Deterioration in Admitted Patients through a Machine Learning Model

Prem Timsina, Max S. Tomlinson, Joel T Dudley, 2020, Journal of clinical medicine.

Machine Learning to Predict Mortality and Critical Events in a Cohort of Patients With COVID-19 in New York City: Model Development and Validation

Kipp W. Johnson, Fayzan F. Chaudhry, Jessica K De Freitas, 2020, Journal of Medical Internet Research.

Development and validation of a machine learning-based prediction model for near-term in-hospital mortality among patients with COVID-19

M. Mazumdar, D. Reich, P. Timsina, 2020, BMJ Supportive & Palliative Care.

Analysis of Interference in Ad-Hoc Networks

Benjamin S. Glicksberg, V. Fuster, N. Weissman, 2003 .

AKI in Hospitalized Patients with COVID-19.

Benjamin S. Glicksberg, A. Just, V. Fuster, 2020, Journal of the American Society of Nephrology : JASN.

Real-time Multi-Modality Clinical Decision Support Platform: An Overview of Incorporating Deep Learning within Multi-Modality Fusion Framework in HealthCare

P. Timsina, A. Kia, 2022 .

Retrospective cohort study of clinical characteristics of 2199 hospitalised patients with COVID-19 in New York City

Kipp W. Johnson, Jessica K De Freitas, Benjamin S. Glicksberg, 2020, BMJ Open.

Using Machine Learning to Predict ICU Transfer in Hospitalized COVID-19 Patients

M. Mazumdar, D. Reich, P. Timsina, 2020, Journal of clinical medicine.

Clinical Characteristics of Hospitalized Covid-19 Patients in New York City

Kipp W. Johnson, Jessica K De Freitas, A. Just, 2020, medRxiv.

Predictive Approaches for Acute Dialysis Requirement and Death in COVID-19

Benjamin S. Glicksberg, Z. Fayad, E. Bottinger, 2021, Clinical journal of the American Society of Nephrology : CJASN.

Machine Learning to Predict Mortality and Critical Events in COVID-19 Positive New York City Patients

Riccardo Miotto, Kipp W. Johnson, Fayzan F. Chaudhry, 2020, medRxiv.

SARS-CoV-2 and Stroke Characteristics

A. Babazadeh, M. Azarpazhooh, G. D. De Marchis, 2021, Stroke.

Risk of stroke in hospitalized SARS-CoV-2 infected patients: A multinational study

V. Abedi, A. Ranta, G. Tsivgoulis, 2020, EBioMedicine.

SARS-CoV-2 and Stroke Characteristics: A Report from the Multinational COVID-19 Stroke Study Group

V. Abedi, A. Ranta, M. Harirchian, 2020, medRxiv.

Acute Kidney Injury in Hospitalized Patients with COVID-19

Benjamin S. Glicksberg, A. Just, M. Danieletto, 2020, medRxiv.

Machine Learning to Predict Mortality and Critical Events in a Cohort of Patients With COVID-19 in New York City: Model Development and Validation

Joseph Finkelstein, Riccardo Miotto, Kipp W. Johnson, 2020, Journal of medical Internet research.

Real-time Machine Learning Alerts to Prevent Escalation of Care: A Pragmatic Clinical Trial

E. Klang, P. Timsina, A. Kia, 2022, medRxiv.

Machine Learning to Predict Mortality and Critical Events in a Cohort of Patients With COVID-19 in New York City: Model Development and Validation (Preprint)

Kipp W. Johnson, Judy H. Cho, A. Just, 2020 .

Implementing a Machine Learning Screening Tool for Malnutrition: Insights From Qualitative Research Applicable to Other Machine Learning–Based Clinical Decision Support Systems

A. Kia, M. besculides, R. Freeman, 2022, JMIR formative research.

Predicting Adult Hospital Admission from Emergency Department Using Machine Learning: An Inclusive Gradient Boosting Model

Benjamin S. Glicksberg, E. Klang, P. Timsina, 2022, Journal of clinical medicine.

Comparative Analysis of a Large Language Model and Machine Learning Method for Prediction of Hospitalization from Nurse Triage Notes: Implications for Machine Learning-based Resource Management

Benjamin S. Glicksberg, E. Klang, E. Zimlichman, 2023, medRxiv.

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

Z. Fayad, A. Kia, R. Freeman, 2023, JMIR formative research.

Real-Time Machine Learning Alerts to Prevent Escalation of Care: A Nonrandomized Clustered Pragmatic Clinical Trial*

A. Kia, R. Kohli-Seth, M. Levin, 2024, Critical care medicine.