Masayuki Nigo, MD, MSc

Associate Professor of Clinical Medicine, Academic Institute
Houston Methodist
Weill Cornell Medical College


Dr. Masayuki Nigo holds an M.D. and a Master of Science in Biomedical Informatics. He began his career in medicine after graduating from Fukui University, Japan, in 2005. Dr. Nigo honed his medical skills through a residency in Japan, followed by an internal medicine residency at Beth Israel Medical Center in New York, completed in 2013.

His expertise in infectious diseases was further cultivated at UTHealth McGovern Medical School, where he completed a fellowship in infectious diseases, and an advanced fellowship focusing on Transplant Infectious Diseases. Dr. Nigo's academic career took a significant stride forward at UTHealth McGovern Medical School, where he was appointed as an Assistant Professor in the Division of Infectious Diseases in 2016 and later elevated to Associate Professor in 2022.

In addition to his clinical and teaching roles, Dr. Nigo expanded his academic horizon by obtaining a Master of Science from the McWilliams School of Biomedical Informatics at UTHealth Houston.

In January 2023, Dr. Nigo embarked on a new chapter in his career by joining the Division of Infectious Diseases, Department of Medicine at Houston Methodist. Here, he continues his journey as an Associate Professor of Clinical Medicine, contributing his extensive knowledge and experience to the field of infectious diseases.

Description of Research

Dr. Nigo’s primary research interest lies in harnessing the vast potential of electronic health record (EHR) datasets to address critical clinical questions encountered at the patient's bedside. Through advanced coding and data analysis techniques, Dr. Nigo's lab explores a broad spectrum of research queries, employing both local and de-identified EHR datasets.

A key focus of his research is in the realm of precision medicine, applying artificial intelligence—particularly deep-learning models—to optimize antimicrobial therapy. His work aims to tailor treatment for high-risk patient populations, focusing on antimicrobial pharmacokinetics and the prediction of drug-resistant bacteria. This is achieved by integrating a wide range of patient-specific features extracted from electronic health records. Dr. Nigo's cutting-edge research is supported by NIH funding.

The Nigo Lab is a collaborative environment, boasting a diverse team of informaticians, fellows, residents, and students from both medical and bioinformatics disciplines. Dr. Nigo places a high value on mentorship and collaboration, fostering a rich learning atmosphere. This has led to successful projects, culminating in publications in peer-reviewed journals.

Areas Of Expertise

Artificial Intelligence Transplant Infectious Diseases Immunocompromised patients Drug Resistant Bacteria Antimicrobial Pharmacokinetics Biomedical Informatics

Single-center Outcomes After Liver Transplantation With SARS-CoV-2–Positive Donors: An Argument for Increased Utilization
Connor, AA, Adelman, MW, Mobley, CM, Moaddab, M, Erhardt, AJ, Hsu, DE, Brombosz, EW, Sanghvi, M, Lee Cheah, Y, Simon, CJ, Hobeika, MJ, Saharia, AS, Victor, DW, Kodali, S, Basra, T, Graviss, EA, Nguyen, DT, Elsaiey, A, Moore, LW, Nigo, M, Drews, AL, Grimes, KA, Arias, CA, Li, XC, Gaber, AO & Ghobrial, RM 2024, , Transplantation Direct, vol. 10, no. 4, pp. E1590.

Deep learning model for personalized prediction of positive MRSA culture using time-series electronic health records
Nigo, M, Rasmy, L, Mao, B, Kannadath, BS, Xie, Z & Zhi, D 2024, , Nature Communications, vol. 15, no. 1, 2036, pp. 2036.

Description of Cryptococcosis Following SARS-CoV-2 Infection: A Disease Survey Through the Mycosis Study Group Education and Research Consortium (MSG-19)
the Mycoses Study Group Education and Research Consortium (MSGERC) Cryptococcal Registry Cohort 2024, , Clinical Infectious Diseases, vol. 78, no. 2, pp. 371-377.

Use of Real-World EMR Data to Rapidly Evaluate Treatment Effects of Existing Drugs for Emerging Infectious Diseases: Remdesivir for COVID-19 Treatment as an Example
Zhang, C, Nigo, M, Patel, S, Yu, D, Septimus, E & Wu, H 2024, , Statistics in Biosciences.

COVID-19 Vaccine Seroresponse Based on The Timing of The Primary Series; Pre- versus Post-Renal Transplantation
Weinberg, AR, Caeg, CO, DePalma, R, Hernandez, F, Rogers, JH, Ibrahim, HN, Bynon, SJ & Nigo, M 2023, , Clinical Transplantation, vol. 37, no. 11, e15072, pp. e15072.

Seroprevalence of Measles, Mumps, Rubella, and Varicella-Zoster Virus and Seroresponse to the Vaccinations in Adult Solid Organ Transplant Candidates
Javaid, H, Prasad, P, De Golovine, A, Hasbun, R, Jyothula, S, Machicao, V, Bynon, JS, Ostrosky, L & Nigo, M 2023, , Transplantation, vol. 107, no. 10, pp. 2279-2284.

Multiple fungating masses on the abdomen due to Actinomyces
Ramirez, D, Covinsky, M, Chávez, V, Millas, SG & Nigo, M 2023, , The Lancet Infectious Diseases, vol. 23, no. 9, pp. e389.

Invasive Mold Infections following Hurricane Harvey—Houston, Texas
Toda, M, Williams, S, Jackson, BR, Wurster, S, Serpa, JA, Nigo, M, Grimes, CZ, Atmar, RL, Chiller, TM, Ostrosky-Zeichner, L & Kontoyiannis, DP 2023, , Open Forum Infectious Diseases, vol. 10, no. 3, ofad093, pp. ofad093.

International Multicenter Study Comparing COVID-19 in Patients With Cancer to Patients Without Cancer: Impact of Risk Factors and Treatment Modalities on Survivorship
Data-Driven Determinants for COVID-19 Oncology Discovery Effort (D3CODE) Team 2023, , eLife, vol. 12, e81127.

A Deep-Learning-based Two-Compartment Predictive Model (PKRNN-2CM) for Vancomycin Therapeutic Drug Monitoring
Mao, B, Xie, Z, Rasmy, L, Nigo, M & Zhi, D 2023, . in Proceedings - 2023 IEEE 11th International Conference on Healthcare Informatics, ICHI 2023. Proceedings - 2023 IEEE 11th International Conference on Healthcare Informatics, ICHI 2023, Institute of Electrical and Electronics Engineers Inc. pp. 484, 11th IEEE International Conference on Healthcare Informatics, ICHI 2023, Houston, United States, 6/26/23.

Human Dectin-1 deficiency impairs macrophage-mediated defense against phaeohyphomycosis
Drummond, RA, Desai, JV, Hsu, AP, Oikonomou, V, Vinh, DC, Acklin, JA, Abers, MS, Walkiewicz, MA, Anzick, SL, Swamydas, M, Vautier, S, Natarajan, M, Oler, AJ, Yamanaka, D, Mayer-Barber, KD, Iwakura, Y, Bianchi, D, Driscoll, B, Hauck, K, Kline, A, Viall, NSP, Zerbe, CS, Ferré, EMN, Schmitt, MM, DiMaggio, T, Pittaluga, S, Butman, JA, Zelazny, AM, Shea, YR, Arias, CA, Ashbaugh, C, Mahmood, M, Temesgen, Z, Theofiles, AG, Nigo, M, Moudgal, V, Bloch, KC, Kelly, SG, Suzanne Whitworth, M, Rao, G, Whitener, CJ, Mafi, N, Gea-Banacloche, J, Kenyon, LC, Miller, WR, Boggian, K, Gilbert, A, Sincock, M, Freeman, AF, Bennett, JE, Hasbun, R, Mikelis, CM, Kwon-Chung, KJ, Belkaid, Y, Brown, GD, Lim, JK, Kuhns, DB, Holland, SM & Lionakis, MS 2022, , Journal of Clinical Investigation, vol. 132, no. 22, e159348.

PK-RNN-V E: A deep learning model approach to vancomycin therapeutic drug monitoring using electronic health record data
Nigo, M, Tran, HTN, Xie, Z, Feng, H, Mao, B, Rasmy, L, Miao, H & Zhi, D 2022, , Journal of Biomedical Informatics, vol. 133, 104166.

Post-Lung Transplantation Outcomes and Ex Vivo Histopathological Findings in Severe Post-COVID-19 Pulmonary Disease-A Single-Center Experience
Javaid, H, Nigo, M, Zhao, B, Trujillo, DO, Hasbun, R, Ostrosky-Zeichner, L, Patel, M & Jyothula, S 2022, , Open Forum Infectious Diseases, vol. 9, no. 9, ofac425.

Comparison of Four International Guidelines on the Utility of Cranial Imaging Before Lumbar Puncture in Adults with Bacterial Meningitis
Park, N, Nigo, M & Hasbun, R 2022, , Clinical Neuroradiology, vol. 32, no. 3, pp. 857-862.

Recurrent neural network models (CovRNN) for predicting outcomes of patients with COVID-19 on admission to hospital: model development and validation using electronic health record data
Rasmy, L, Nigo, M, Kannadath, BS, Xie, Z, Mao, B, Patel, K, Zhou, Y, Zhang, W, Ross, A, Xu, H & Zhi, D 2022, , The Lancet Digital Health, vol. 4, no. 6, pp. e415-e425.

Characteristics, safety and cost-effectiveness analysis of self-administered outpatient parenteral antibiotic therapy via a disposable elastomeric continuous infusion pump at two county hospitals in Houston, Texas, United States
Karimaghaei, S, Rao, A, Chijioke, J, Finch, N & Nigo, M 2022, , Journal of Clinical Pharmacy and Therapeutics, vol. 47, no. 2, pp. 211-217.

Real World Long-term Assessment of The Efficacy of Tocilizumab in Patients with COVID-19: Results From A Large De-identified Multicenter Electronic Health Record Dataset in the United States
Nigo, M, Rasmy, L, May, SB, Rao, A, Karimaghaei, S, Kannadath, BS, De la Hoz, A, Arias, CA, Li, L & Zhi, D 2021, , International Journal of Infectious Diseases, vol. 113, pp. 148-154.

Distinguishing cytomegalovirus meningoencephalitis from other viral central nervous system infections
Handley, G, Pankow, S, Bard, JD, Yee, R, Nigo, M & Hasbun, R 2021, , Journal of Clinical Virology, vol. 142, 104936.

Risk Classification for Respiratory Viral Infections in Adult Solid Organ Transplantation Recipients
Samannodi, M, Vaghefi-Hosseini, R, Nigo, M, Guevara, EY & Hasbun, R 2021, , Transplantation Proceedings, vol. 53, no. 2, pp. 737-742.

Seroprevalence of Strongyloides stercoralis and Evaluation of Universal Screening in Kidney Transplant Candidates: A Single-Center Experience in Houston (2012-2017)
Al-Obaidi, M, Hasbun, R, Vigil, KJ, Edwards, AR, Chavez, V, Hall, DR, Dar, WA, De Golovine, A, Ostrosky-Zeichner, L, Bynon, JS & Nigo, M 2019, , Open Forum Infectious Diseases, vol. 6, no. 7, ofz172.