Visual Analytics to Leverage Anesthesia Electronic Health Record.

Link: https://doi.org/10.1213/ANE.0000000000006175 Authors: Kahn, Ronald A; Gal, Jonathan S; Hofer, Ira S; Wax, David B; Villar, Joshua I; Levin, Mathew A Abstract: Visual analytics is the science of analytical reasoning supported by interactive visual interfaces called dashboards. In this report, we describe our experience addressing the challenges in visual analytics of anesthesia electronic health record…

Read More

Human WDR5 promotes breast cancer growth and metastasis via KMT2-independent translation regulation.

Link: https://doi.org/10.7554/eLife.78163 Authors: Cai, Wesley L; Chen, Jocelyn Fang-Yi; Chen, Huacui; Wingrove, Emily; Kurley, Sarah J; Chan, Lok Hei; Zhang, Meiling; Arnal-Estape, Anna; Zhao, Minghui; Balabaki, Amer; Li, Wenxue; Yu, Xufen; Krop, Ethan D; Dou, Yali; Liu, Yansheng; Jin, Jian; Westbrook, Thomas F; Nguyen, Don X; Yan, Qin Abstract: Metastatic breast cancer remains a major…

Read More

Modulation of the Association Between Age and Death by Risk Factor Burden in Critically Ill Patients With COVID-19.

Link: https://doi.org/10.1097/CCE.0000000000000755 Authors: Sunderraj, Ashwin; Cho, Chloe; Cai, Xuan; Gupta, Shruti; Mehta, Rupal; Isakova, Tamara; Leaf, David E; Srivastava, Anand; , Abstract: Older age is a key risk factor for adverse outcomes in critically ill patients with COVID-19. However, few studies have investigated whether preexisting comorbidities and acute physiologic ICU factors modify the association between…

Read More

Proteomic Characterization of Acute Kidney Injury in Patients Hospitalized with SARS-CoV2 Infection.

Link: https://doi.org/10.1101/2021.12.09.21267548 Authors: Paranjpe, Ishan; Jayaraman, Pushkala; Su, Chen-Yang; Zhou, Sirui; Chen, Steven; Thompson, Ryan; Del Valle, Diane Marie; Kenigsberg, Ephraim; Zhao, Shan; Jaladanki, Suraj; Chaudhary, Kumardeep; Ascolillo, Steven; Vaid, Akhil; Kumar, Arvind; Kozlova, Edgar; Paranjpe, Manish; O’Hagan, Ross; Kamat, Samir; Gulamali, Faris F; Kauffman, Justin; Xie, Hui; Harris, Joceyln; Patel, Manishkumar; Argueta, Kimberly; Batchelor,…

Read More

Assessment of prescribed vs. achieved fluid balance during continuous renal replacement therapy and mortality outcome.

Link: https://doi.org/10.1371/journal.pone.0272913 Authors: 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 Abstract: Fluid management during continuous renal replacement therapy (CRRT) requires accuracy in the prescription of desired patient fluid balance (FBGoal) and precision in the attainable patient…

Read More

Enhancing convolutional neural network predictions of electrocardiograms with left ventricular dysfunction using a novel sub-waveform representation.

Link: https://doi.org/10.1016/j.cvdhj.2022.07.074 Authors: Honarvar, Hossein; Agarwal, Chirag; Somani, Sulaiman; Vaid, Akhil; Lampert, Joshua; Wanyan, Tingyi; Reddy, Vivek Y; Nadkarni, Girish N; Miotto, Riccardo; Zitnik, Marinka; Wang, Fei; Glicksberg, Benjamin S Abstract: Electrocardiogram (ECG) deep learning (DL) has promise to improve the outcomes of patients with cardiovascular abnormalities. In ECG DL, researchers often use convolutional neural…

Read More

Machine learning for risk stratification in kidney disease.

Link: https://doi.org/10.1097/MNH.0000000000000832 Authors: Gulamali, Faris F; Sawant, Ashwin S; Nadkarni, Girish N Abstract: Risk stratification for chronic kidney is becoming increasingly important as a clinical tool for both treatment and prevention measures. The goal of this review is to identify how machine learning tools contribute and facilitate risk stratification in the clinical setting. The two…

Read More

Federated Learning in Risk Prediction: A Primer and Application to COVID-19-Associated Acute Kidney Injury.

Link: https://doi.org/10.1159/000525645 Authors: Gulamali, Faris F; Nadkarni, Girish N Abstract: Modern machine learning and deep learning algorithms require large amounts of data; however, data sharing between multiple healthcare institutions is limited by privacy and security concerns. Federated learning provides a functional alternative to the single-institution approach while avoiding the pitfalls of data sharing. In cross-silo…

Read More