Introduction to Artificial Intelligence and Machine Learning in Nephrology von Nadkarni, Girish N

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Deep learning and the electrocardiogram: review of the current state-of-the-art von Somani, Sulaiman, Russak, Adam J, Richter, Felix, Zhao, Shan, Vaid, Akhil, Chaudhry, Fayzan, De Freitas, Jessica K, Naik, Nidhi, Miotto, Riccardo, Nadkarni, Girish N, Narula, Jagat, Argulian, Edgar, Glicksberg, Benjamin S

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Distinct subtypes of polycystic ovary syndrome with novel genetic associations: An unsupervised, phenotypic clustering analysis von Dapas, Matthew, Lin, Frederick T J, Nadkarni, Girish N, Sisk, Ryan, Legro, Richard S, Urbanek, Margrit, Hayes, M Geoffrey, Dunaif, Andrea

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Advanced glycation end products dietary restriction effects on bacterial gut microbiota in peritoneal dialysis patients; a randomized open label controlled trial von Yacoub, Rabi, Nugent, Melinda, Cai, Weijin, Nadkarni, Girish N, Chaves, Lee D, Abyad, Sham, Honan, Amanda M, Thomas, Shruthi A, Zheng, Wei, Valiyaparambil, Sujith A, Bryniarski, Mark A, Sun, Yijun, Buck, Michael, Genco, Robert J, Quigg, Richard J, He, John C, Uribarri, Jaime

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Acute Kidney Injury in Patients on SGLT2 Inhibitors: A Propensity-Matched Analysis von Nadkarni, Girish N, Ferrandino, Rocco, Chang, Alexander, Surapaneni, Aditya, Chauhan, Kinsuk, Poojary, Priti, Saha, Aparna, Ferket, Bart, Grams, Morgan E, Coca, Steven G

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Plasma Biomarkers and Kidney Function Decline in Early and Established Diabetic Kidney Disease von Coca, Steven G, Nadkarni, Girish N, Huang, Yuan, Moledina, Dennis G, Rao, Veena, Zhang, Jane, Ferket, Bart, Crowley, Susan T, Fried, Linda F, Parikh, Chirag R

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Kidney-Failure Risk Projection for the Living Kidney-Donor Candidate von Grams, Morgan E, Sang, Yingying, Levey, Andrew S, Matsushita, Kunihiro, Ballew, Shoshana, Chang, Alex R, Chow, Eric K.H, Kasiske, Bertram L, Kovesdy, Csaba P, Nadkarni, Girish N, Shalev, Varda, Segev, Dorry L, Coresh, Josef, Lentine, Krista L, Garg, Amit X

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Characterization of Patients Who Return to Hospital Following Discharge from Hospitalization for COVID-19 von Somani, Sulaiman S., Richter, Felix, Fuster, Valentin, De Freitas, Jessica K., Naik, Nidhi, Sigel, Keith, Bottinger, Erwin P, Levin, Matthew A., Fayad, Zahi, Just, Allan C., Charney, Alexander W., Zhao, Shan, Glicksberg, Benjamin S., Lala, Anuradha, Nadkarni, Girish N.

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Derivation and validation of a machine learning risk score using biomarker and electronic patient data to predict progression of diabetic kidney disease von Chan, Lili, Nadkarni, Girish N., Fleming, Fergus, McCullough, James R., Connolly, Patricia, Mosoyan, Gohar, El Salem, Fadi, Kattan, Michael W., Vassalotti, Joseph A., Murphy, Barbara, Donovan, Michael J., Coca, Steven G., Damrauer, Scott M.

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Use of Physiological Data From a Wearable Device to Identify SARS-CoV-2 Infection and Symptoms and Predict COVID-19 Diagnosis: Observational Study von Hirten, Robert P., Danieletto, Matteo, Tomalin, Lewis, Choi, Katie Hyewon, Zweig, Micol, Golden, Eddye, Kaur, Sparshdeep, Helmus, Drew, Biello, Anthony, Pyzik, Renata, Charney, Alexander, Miotto, Riccardo, Glicksberg, Benjamin S., Levin, Matthew, Nabeel, Ismail, Aberg, Judith, Reich, David, Charney, Dennis, Bottinger, Erwin P., Keefer, Laurie, Suarez-Farinas, Mayte, Nadkarni, Girish N., Fayad, Zahi A.

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Rate of Correction of Hypernatremia and Health Outcomes in Critically Ill Patients von Chauhan, Kinsuk, Pattharanitima, Pattharawin, Patel, Niralee, Duffy, Aine, Saha, Aparna, Chaudhary, Kumardeep, Debnath, Neha, Van Vleck, Tielman, Chan, Lili, Nadkarni, Girish N, Coca, Steven G

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Population-Based Penetrance of Deleterious Clinical Variants von Forrest, Iain S, Chaudhary, Kumardeep, Vy, Ha My T, Petrazzini, Ben O, Bafna, Shantanu, Jordan, Daniel M, Rocheleau, Ghislain, Loos, Ruth J. F, Nadkarni, Girish N, Cho, Judy H, Do, Ron

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Effect of Intensive Blood Pressure Lowering on Kidney Tubule Injury: Findings From the ACCORD Trial Study Participants von Nadkarni, Girish N., Chauhan, Kinsuk, Rao, Veena, Ix, Joachim H., Shlipak, Michael G., Parikh, Chirag R., Coca, Steven G.

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A machine learning model identifies patients in need of autoimmune disease testing using electronic health records von Forrest, Iain S., Petrazzini, Ben O., Duffy, Áine, Park, Joshua K., O’Neal, Anya J., Jordan, Daniel M., Rocheleau, Ghislain, Nadkarni, Girish N., Cho, Judy H., Blazer, Ashira D., Do, Ron

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Local large language models for privacy-preserving accelerated review of historic echocardiogram reports von Vaid, Akhil, Duong, Son Q, Lampert, Joshua, Kovatch, Patricia, Freeman, Robert, Argulian, Edgar, Croft, Lori, Lerakis, Stamatios, Goldman, Martin, Khera, Rohan, Nadkarni, Girish N

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Comparison of predicting cardiovascular disease hospitalization using individual, ZIP code-derived, and machine learning model-predicted educational attainment in New York City von Takkavatakarn, Kullaya, Dai, Yang, Hsun Wen, Huei, Kauffman, Justin, Charney, Alexander, Coca, Steven G, Nadkarni, Girish N, Chan, Lili

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Assessment of prescribed vs. achieved fluid balance during continuous renal replacement therapy and mortality outcome von Neyra, Javier A, Lambert, Joshua, Ortiz-Soriano, Victor, Cleland, Daniel, Colquitt, Jon, Adams, Paul, Bissell, Brittany D, Chan, Lili, Nadkarni, Girish N, Tolwani, Ashita, Goldstein, Stuart L

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The prognostic importance of duration of AKI: a systematic review and meta-analysis von Mehta, Swati, Chauhan, Kinsuk, Patel, Achint, Patel, Shanti, Pinotti, Rachel, Nadkarni, Girish N, Parikh, Chirag R, Coca, Steven G

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Evaluating prompt engineering on GPT-3.5’s performance in USMLE-style medical calculations and clinical scenarios generated by GPT-4 von Patel, Dhavalkumar, Raut, Ganesh, Zimlichman, Eyal, Cheetirala, Satya Narayan, Nadkarni, Girish N, Glicksberg, Benjamin S., Apakama, Donald U., Bell, Elijah J., Freeman, Robert, Timsina, Prem, Klang, Eyal

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Machine learning models to predict end-stage kidney disease in chronic kidney disease stage 4 von Takkavatakarn, Kullaya, Oh, Wonsuk, Cheng, Ella, Nadkarni, Girish N, Chan, Lili

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