Posts Tagged ‘Bioinformatics’
Integrated multiomics implicates dysregulation of ECM and cell adhesion pathways as drivers of severe COVID-associated kidney injury.
Link: https://doi.org/10.1101/2024.03.18.24304401 Authors: Anandakrishnan, Nanditha; Yi, Zhengzi; Sun, Zeguo; Liu, Tong; Haydak, Jonathan; Eddy, Sean; Jayaraman, Pushkala; DeFronzo, Stefanie; Saha, Aparna; Sun, Qian; Yang, Dai; Mendoza, Anthony; Mosoyan, Gohar; Wen, Huei Hsun; Schaub, Jennifer A; Fu, Jia; Kehrer, Thomas; Menon, Rajasree; Otto, Edgar A; Godfrey, Bradley; Suarez-Farinas, Mayte; Leffters, Sean; Twumasi, Akosua; Meliambro, Kristin; Charney,…
Read MoreUtilizing large language models in breast cancer management: systematic review.
Link: https://doi.org/10.1007/s00432-024-05678-6 Authors: Sorin, Vera; Glicksberg, Benjamin S; Artsi, Yaara; Barash, Yiftach; Konen, Eli; Nadkarni, Girish N; Klang, Eyal Abstract: Despite advanced technologies in breast cancer management, challenges remain in efficiently interpreting vast clinical data for patient-specific insights. We reviewed the literature on how large language models (LLMs) such as ChatGPT might offer solutions in…
Read MoreA Multimodality Video-Based AI Biomarker For Aortic Stenosis Development And Progression.
Link: https://doi.org/10.1101/2023.09.28.23296234 Authors: Oikonomou, Evangelos K; Holste, Gregory; Yuan, Neal; Coppi, Andreas; McNamara, Robert L; Haynes, Norrisa; Vora, Amit N; Velazquez, Eric J; Li, Fan; Menon, Venu; Kapadia, Samir R; Gill, Thomas M; Nadkarni, Girish N; Krumholz, Harlan M; Wang, Zhangyang; Ouyang, David; Khera, Rohan Abstract: Aortic stenosis (AS) is a major public health challenge…
Read MoreAssociations between Sperm Epigenetic Age and Semen Parameters: An Evaluation of Clinical and Non-Clinical Cohorts.
Link: https://doi.org/10.3390/cimb46020101 Authors: Sawant, Savni; Oluwayiose, Oladele A; Nowak, Karolina; Maxwell, DruAnne L; Houle, Emily; Paskavitz, Amanda L; Saddiki, Hachem; Bertolla, Ricardo P; Pilsner, J Richard Abstract:
Read MoreRemote Monitoring and Artificial Intelligence: Outlook for 2050.
Link: https://doi.org/10.1213/ANE.0000000000006712 Authors: Feinstein, Max; Katz, Daniel; Demaria, Samuel; Hofer, Ira S Abstract: Remote monitoring and artificial intelligence will become common and intertwined in anesthesiology by 2050. In the intraoperative period, technology will lead to the development of integrated monitoring systems that will integrate multiple data streams and allow anesthesiologists to track patients more effectively.…
Read MoreDevelopment of the ehive Digital Health App: Protocol for a Centralized Research Platform.
Link: https://doi.org/10.2196/49204 Authors: Hirten, Robert P; Danieletto, Matteo; Landell, Kyle; Zweig, Micol; Golden, Eddye; Orlov, Georgy; Rodrigues, Jovita; Alleva, Eugenia; Ensari, Ipek; Bottinger, Erwin; Nadkarni, Girish N; Fuchs, Thomas J; Fayad, Zahi A Abstract: The increasing use of smartphones, wearables, and connected devices has enabled the increasing application of digital technologies for research. Remote digital…
Read MorePeripheral Transcriptomics in Acute and Long-Term Kidney Dysfunction in SARS-CoV2 Infection.
Link: https://doi.org/10.1101/2023.10.25.23297469 Authors: Jayaraman, Pushkala; Rajagopal, Madhumitha; Paranjpe, Ishan; Liharska, Lora; Suarez-Farinas, Mayte; Thompson, Ryan; Del Valle, Diane Marie; Beckmann, Noam; Oh, Wonsuk; Gulamali, Faris F; Kauffman, Justin; Gonzalez-Kozlova, Edgar; Dellepiane, Sergio; Vasquez-Rios, George; Vaid, Akhil; Jiang, Joy; Chen, Annie; Sakhuja, Ankit; Chen, Steven; Kenigsberg, Ephraim; He, John Cijiang; Coca, Steven G; Chan, Lili; Schadt,…
Read MoreCirculating Metabolomic Associations with Neurocognitive Outcomes in Pediatric CKD.
Link: https://doi.org/10.2215/CJN.0000000000000318 Authors: Lee, Arthur M; Xu, Yunwen; Hooper, Stephen R; Abraham, Alison G; Hu, Jian; Xiao, Rui; Matheson, Matthew B; Brunson, Celina; Rhee, Eugene P; Coresh, Josef; Vasan, Ramachandran S; Schrauben, Sarah; Kimmel, Paul L; Warady, Bradley A; Furth, Susan L; Hartung, Erum A; Denburg, Michelle R; , Abstract: Children with CKD are at…
Read MoreA clustering approach to improve our understanding of the genetic and phenotypic complexity of chronic kidney disease.
Link: https://doi.org/10.21203/rs.3.rs-3424565/v1 Authors: Eoli, Andrea; Ibing, Susanne; Schurmann, Claudia; Nadkarni, Girish N; Heyne, Henrike; Böttinger, Erwin Abstract: Chronic kidney disease (CKD) is a complex disorder that causes a gradual loss of kidney function, affecting approximately 9.1% of the world’s population. Here, we use a soft-clustering algorithm to deconstruct its genetic heterogeneity. First, we selected 322…
Read MoreA clustering approach to improve our understanding of the genetic and phenotypic complexity of chronic kidney disease.
Link: https://doi.org/10.1101/2023.10.12.23296926 Authors: Eoli, A; Ibing, S; Schurmann, C; Nadkarni, G N; Heyne, H O; Böttinger, E Abstract: Chronic kidney disease (CKD) is a complex disorder that causes a gradual loss of kidney function, affecting approximately 9.1% of the world’s population. Here, we use a soft-clustering algorithm to deconstruct its genetic heterogeneity. First, we selected…
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