Research output per year
Research output per year
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Dive into the research topics where The Charles Bronfman Institute for Personalized Medicine is active. These topic labels come from the works of this organization's members. Together they form a unique fingerprint.
Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
Profiles
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Judy Cho
- Artificial Intelligence and Human Health
- Cancer Prevention & Control
- Friedman Brain Institute
- Genetics and Genomic Sciences
- Graduate School of Biomedical Sciences
- Icahn Genomics Institute
- Icahn School of Medicine at Mount Sinai
- Marc and Jennifer Lipschultz Precision Immunology Institute
- Medicine
- Medicine - Gastroenterology
- The Charles Bronfman Institute for Personalized Medicine
- The Tisch Cancer Institute
Person
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Yuval Itan
- Center for Inborn Errors of Immunity
- Friedman Brain Institute
- Genetics and Genomic Sciences
- Graduate School of Biomedical Sciences
- Icahn Genomics Institute
- Icahn School of Medicine at Mount Sinai
- Mindich Child Health and Development Institute
- The Charles Bronfman Institute for Personalized Medicine
Person
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Girish Nadkarni
- The Charles Bronfman Institute for Personalized Medicine
- Institute for Health Equity Research
- Artificial Intelligence and Human Health
- Division of Data-Driven and Digital Medicine
- Graduate School of Biomedical Sciences
- Hasso Plattner Institute for Digital Health at Mount Sinai
- Icahn School of Medicine at Mount Sinai
- Medicine
- Medicine - Nephrology
- Mount Sinai Clinical Intelligence Institute
- Nephrology T32
Person
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Guo-Cheng Yuan
- Institute for Regenerative Medicine
- Cancer Immunology
- The Tisch Cancer Institute
- Graduate School of Biomedical Sciences
- Black Family Stem Cell Institute
- Genetics and Genomic Sciences
- Icahn Genomics Institute
- Icahn School of Medicine at Mount Sinai
- Marc and Jennifer Lipschultz Precision Immunology Institute
- The Charles Bronfman Institute for Personalized Medicine
Person
Research output
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A clustering approach to improve our understanding of the genetic and phenotypic complexity of chronic kidney disease
Eoli, A., Ibing, S., Schurmann, C., Nadkarni, G. N., Heyne, H. O. & Böttinger, E., Dec 2024, In: Scientific Reports. 14, 1, 9642.Research output: Contribution to journal › Article › peer-review
Open Access -
A Deep Intronic PKHD1 Variant Identified by SpliceAI in a Deceased Neonate With Autosomal Recessive Polycystic Kidney Disease
Richter, F., Rutherford, K. D., Cooke, A. J., Meshkati, M., Eddy-Abrams, V., Greene, D., Kosowsky, J., Park, Y., Aggarwal, S., Burke, R. J., Chang, W., Connors, J., Giannone, P. J., Hays, T., Khattar, D., Polak, M., Senaldi, L., Smith-Raska, M., Sridhar, S. & Steiner, L. & 5 others, , Jun 2024, In: American Journal of Kidney Diseases. 83, 6, p. 829-833 5 p.Research output: Contribution to journal › Article › peer-review
2 Scopus citations -
A foundation model for clinician-centered drug repurposing
Huang, K., Chandak, P., Wang, Q., Havaldar, S., Vaid, A., Leskovec, J., Nadkarni, G. N., Glicksberg, B. S., Gehlenborg, N. & Zitnik, M., 2024, (Accepted/In press) In: Nature Medicine.Research output: Contribution to journal › Article › peer-review
Open Access -
A genetic association study of circulating coagulation factor VIII and von Willebrand factor levels
Trans-Omics for Precision Medicine (TOPMed) program & The INVENT Consortium, 2 May 2024, In: Blood. 143, 18, p. 1845-1855 11 p.Research output: Contribution to journal › Article › peer-review
Open Access2 Scopus citations -
A Multimodal Video-Based AI Biomarker for Aortic Stenosis Development and Progression
Oikonomou, E. K., Holste, G., Yuan, N., Coppi, A., McNamara, R. L., Haynes, N. A., Vora, A. N., Velazquez, E. J., Li, F., Menon, V., Kapadia, S. R., Gill, T. M., Nadkarni, G. N., Krumholz, H. M., Wang, Z., Ouyang, D. & Khera, R., 12 Jun 2024, In: JAMA Cardiology. 9, 6, p. 534-544 11 p.Research output: Contribution to journal › Article › peer-review
3 Scopus citations -
A novel method leveraging time series data to improve subphenotyping and application in critically ill patients with COVID-19
Oh, W., Jayaraman, P., Tandon, P., Chaddha, U. S., Kovatch, P., Charney, A. W., Glicksberg, B. S. & Nadkarni, G. N., Feb 2024, In: Artificial Intelligence in Medicine. 148, 102750.Research output: Contribution to journal › Article › peer-review
1 Scopus citations -
Applications of large language models in psychiatry: a systematic review
Omar, M., Soffer, S., Charney, A. W., Landi, I., Nadkarni, G. N. & Klang, E., 2024, In: Frontiers in Psychiatry. 15, 1422807.Research output: Contribution to journal › Review article › peer-review
Open Access -
A Real-World Precision Medicine Program Including the KidneyIntelX Test Effectively Changes Management Decisions and Outcomes for Patients With Early-Stage Diabetic Kidney Disease
Tokita, J., Lam, D., Vega, A., Wang, S., Amoruso, L., Muller, T., Naik, N., Rathi, S., Martin, S., Zabetian, A., Liu, C., Sinfield, C., McNicholas, T., Fleming, F., Coca, S. G., Nadkarni, G. N., Tun, R., Kattan, M., Donovan, M. J. & Rahim, A. K., 1 Jan 2024, In: Journal of Primary Care and Community Health. 15Research output: Contribution to journal › Article › peer-review
Open Access -
Artificial Intelligence for Cardiovascular Care—Part 1: Advances: JACC Review Topic of the Week
Elias, P., Jain, S. S., Poterucha, T., Randazzo, M., Lopez Jimenez, F., Khera, R., Perez, M., Ouyang, D., Pirruccello, J., Salerno, M., Einstein, A. J., Avram, R., Tison, G. H., Nadkarni, G., Natarajan, V., Pierson, E., Beecy, A., Kumaraiah, D., Haggerty, C. & Avari Silva, J. N. & 1 others, , 18 Jun 2024, In: Journal of the American College of Cardiology. 83, 24, p. 2472-2486 15 p.Research output: Contribution to journal › Review article › peer-review
6 Scopus citations -
Artificial Intelligence in Cardiovascular Care—Part 2: Applications: JACC Review Topic of the Week
Jain, S. S., Elias, P., Poterucha, T., Randazzo, M., Lopez Jimenez, F., Khera, R., Perez, M., Ouyang, D., Pirruccello, J., Salerno, M., Einstein, A. J., Avram, R., Tison, G. H., Nadkarni, G., Natarajan, V., Pierson, E., Beecy, A., Kumaraiah, D., Haggerty, C. & Avari Silva, J. N. & 1 others, , 18 Jun 2024, In: Journal of the American College of Cardiology. 83, 24, p. 2487-2496 10 p.Research output: Contribution to journal › Review article › peer-review
6 Scopus citations -
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., Hofer, I. S., Nadkarni, G. N., Timsina, P., Kia, A. & Levin, M. A., Dec 2024, In: npj Digital Medicine. 7, 1, 149.Research output: Contribution to journal › Article › peer-review
Open Access -
Assessing GPT-4 multimodal performance in radiological image analysis
Brin, D., Sorin, V., Barash, Y., Konen, E., Glicksberg, B. S., Nadkarni, G. N. & Klang, E., 2024, (Accepted/In press) In: European Radiology.Research output: Contribution to journal › Article › peer-review
Open Access
Press/Media
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Reports Summarize Liver Fibrosis Findings from Icahn School of Medicine at Mount Sinai (Comparison of Blood-based Liver Fibrosis Scores In the Mount Sinai Health System, Masld Registry, and Nhanes 2017-2020 Study)
Nadkarni, G., Rocheleau, G., Do, R. & Bansal, M.
25/09/24
1 item of Media coverage
Press/Media
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Study Results from Icahn School of Medicine at Mount Sinai Provide New Insights into Intracranial Hypertension (Derivation, external and clinical validation of a deep learning approach for detecting intracranial hypertension)
Jayaraman, P., Nadkarni, G., Kovatch, P., Charney, A., Dangayach, N., Reynolds, A., Duong, S. Q., Hofer, I. & Sakhuja, A.
24/09/24
1 item of Media coverage
Press/Media
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Deep learning tool could improve brain pressure monitoring
12/09/24
1 item of Media coverage
Press/Media
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New Long QT Syndrome Study Results from Icahn School of Medicine at Mount Sinai Described (Multimodal fusion learning for long QT syndrome pathogenic genotypes in a racially diverse population)
Jayaraman, P., Reddy, V. Y., Kovatch, P., Do, R. & Charney, A.
9/09/24
1 item of Media coverage
Press/Media
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AI-driven tool could improve brain pressure monitoring in intensive care patients
6/09/24
1 item of Media coverage
Press/Media
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AI Detects Intracranial Hypertension Without Invasive Procedures
Jayaraman, P., Nadkarni, G., Kovatch, P., Reich, D., Charney, A., Dangayach, N., Reynolds, A., Duong, S. Q., Hofer, I. & Sakhuja, A.
6/09/24
1 item of Media coverage
Press/Media
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AI-Driven Tool to Revolutionize Brain Pressure Monitoring in Intensive Care Patients
6/09/24
1 item of Media coverage
Press/Media
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Mount Sinai Health System: New AI-Driven Tool Could Revolutionize Brain Pressure Monitoring in Intensive Care Patients
Jayaraman, P., Nadkarni, G., Kovatch, P., Reich, D., Charney, A., Dangayach, N., Reynolds, A., Duong, S. Q., Hofer, I. & Sakhuja, A.
6/09/24
1 item of Media coverage
Press/Media
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News Brain Pressure Monitoring in Intensive Care Patients Could Be Revolutionized by AI Tool
6/09/24
1 item of Media coverage
Press/Media
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New AI-Driven Tool Could Revolutionize Brain Pressure Monitoring in Intensive Care Patients
Jayaraman, P., Nadkarni, G., Kovatch, P., Reich, D., Charney, A., Dangayach, N., Reynolds, A., Duong, S. Q., Hofer, I. & Sakhuja, A.
5/09/24
2 items of Media coverage
Press/Media
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AI Tool May Transform Brain Pressure Monitoring in ICU
Jayaraman, P., Nadkarni, G., Kovatch, P., Reich, D., Charney, A., Dangayach, N., Reynolds, A., Duong, S. Q., Hofer, I. & Sakhuja, A.
5/09/24
1 item of Media coverage
Press/Media