Sanjat Kanjilal

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Lecturer

Harvard Medical School and Harvard Pilgrim Health Care Institute

United States

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About

Dr. Sanjat Kanjilal is a Lecturer at Harvard Medical School and the Harvard Pilgrim Healthcare Institute in the United States. His research focuses on antimicrobial resistance, including the socio-economic disparities affecting its prevalence, and the clinical implications of viral infections such as SARS-CoV-2. Recent publications include studies on the dynamics of antibiotic resistance and the diagnostic utility of microbial cell-free DNA sequencing.

Recent Grants

Grant: Close

Improving antibiotic treatment decisions through machine learning

Open Date: 2021-07-02

Close Date: 2024-06-30

Grant: Close

Epicenter V: Harvard Pilgrim Health Care Institute Center for Excellence in HAI Surveillance and Prevention

Open Date: 2021-06-01

Close Date: 2026-05-31

Grant: Close

Improving the diagnosis and management of antibiotic resistant infections through machine learning

Open Date: 2018-10-01

Close Date: 2020-10-01

Grant: Close

Optimizing Antibiotic Therapy through Machine Learning Models

Open Date: 2018-04-01

Close Date: 2019-04-01

Grant: Close

Population dynamics of Staphylococcus aureus

Open Date: 2015-07-01

Close Date: 2017-06-01

Articles (22)

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2021

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2020

Collaborators (10)

Mihai Pop

Professor

University of Maryland at College Park

UNITED STATES

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Lynn Bry

Associate Professor

Harvard Medical School

UNITED STATES

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David Helekal

Harvard University

UNITED STATES

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Fateme Nateghi Haredasht

Stanford University

UNITED STATES

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Tom Chen

Assistant Professor

Stanford Health Care

UNITED STATES

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Cormac Kinsella

University of Oxford

UNITED KINGDOM

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James Hay

University of Oxford

UNITED KINGDOM

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Michael Mina

Assistant Professor

UNITED STATES

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Stephen P. Ma

Clinical Assistant Professor

Stanford University

UNITED STATES

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Lee Kennedy-Shaffer

Assistant Professor

Vassar College

UNITED STATES

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Sanjat Kanjilal

Research Interests

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About

Recent Grants

Articles (22)

Antibiotic Resistance Microbiology Dataset (ARMD): A Resource for Antimicrobial Resistance from EHRs

Morbidity and Mortality of Hospital-Onset SARS-CoV-2 Infections Due to Omicron Versus Prior Variants

Morbidity and Mortality of Hospital-Onset SARS-CoV-2 Infections Due to Omicron Versus Prior Variants : A Propensity-Matched Analysis.

Socioeconomic Disparities and the Prevalence of Antimicrobial Resistance

The modern alchemy of clinical pathology: turning the output of microbiology laboratory operations into gold

Cycle threshold dynamics of non–severe acute respiratory coronavirus virus 2 (SARS-CoV-2) respiratory viruses

Flying Into the Future With Large Language Models

<i>Staphylococcus aureus</i> Tetracycline Resistance and Co-resistance in a Doxycycline Postexposure Prophylaxis–Eligible Population

The diagnostic and clinical utility of microbial cell-free DNA sequencing in a real-world setting.

Viral Lineages in the 2022 RSV Surge in the United States.

Impact of direct disk-diffusion testing on time to optimal antibiotic therapy

Structural basis for continued antibody evasion by the SARS-CoV-2 receptor binding domain.

The Effect of Vaccine Type and SARS-CoV-2 Lineage on Commercial SARS-CoV-2 Serologic and Pseudotype Neutralization Assays in mRNA Vaccine Recipients

Estimating epidemiologic dynamics from cross-sectional viral load distributions

Genomic Drivers of Multidrug-Resistant Shigella Affecting Vulnerable Patient Populations in the United States and Abroad

Safety of Live-Attenuated Measles, Mumps, and Rubella Vaccine Administered Within 2 Years of Hematopoietic Cell Transplant.

Enhanced Virus Detection and Metagenomic Sequencing in Patients with Meningitis and Encephalitis.

Prospective Clinical Assessments of Hospitalized Patients With Positive SARS-CoV-2 PCR Tests for Necessity of Isolation.

How SARS-CoV-2 Transformed the Clinical Laboratory: Challenges and Lessons Learned.

The Effect of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Mitigation Strategies on Seasonal Respiratory Viruses: A Tale of 2 Large Metropolitan Centers in the United States.

Applications of machine learning to the problem of antimicrobial resistance: An emerging model for translational research.

Diagnostic Approach for Arboviral Infections in the United States.

Collaborators (10)

Mihai Pop

Lynn Bry

David Helekal

Fateme Nateghi Haredasht

Tom Chen

Cormac Kinsella

James Hay

Michael Mina

Stephen P. Ma

Lee Kennedy-Shaffer

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