Results 191 to 200 of about 246,202 (334)

Application of artificial neural network to predict graft survival after kidney transplantation: Reports of 22 years follow up of 316 patients in Isfahan

, 2009
Mahdi Ashrafi, Mohammad Taghi Hamidi Beheshti, Shahidi Sh., Fereshteh Ashrafi   +3 more
openalex   +1 more source

Catechol Derivative‐Based Bioadhesives: Molecular Design for Precision Medical Adhesion

Advanced Science, EarlyView.
This study utilizes tree‐inspired side‐chain engineering to graft five catechol derivatives onto PVA, systematically revealing how side‐chain length and substituents regulate adhesion and cohesion properties. Among them, the PVA‐CA patch demonstrates superior tissue adhesion, biocompatibility, and promotes regeneration, establishing a programmable ...
Xueyu Wang, Zixin Yang, Shan Wang, Weiwei Tan, Zhirui He, Qinyu Duan, Huanan Wang, Tao Chen, Shanshan Hu   +8 more
wiley   +1 more source

A Study of Mass Transport Towards the Design and Characterization of an Artificial Kidney

, 2014
Peter Soler
openalex   +1 more source

A Subset of Pro‐inflammatory CXCL10+ LILRB2+ Macrophages Derives From Recipient Monocytes and Drives Renal Allograft Rejection

Advanced Science, EarlyView.
This study uncovers a recipient‐derived monocyte‐to‐macrophage trajectory that drives inflammation during kidney transplant rejection. Using over 150 000 single‐cell profiles and more than 850 biopsies, the authors identify CXCL10+ macrophages as key predictors of graft loss.
Alexis Varin, Jovanne Palvair, Lennie Messager, Jamal Bamoulid, Jasper Callemeyn, Mélanie Chaintreuil, Ludivine Dal Zuffo, Didier Ducloux, Imane Farhat, Mathieu Legendre, Laurent Martin, Florian Renosi, Xavier Roussel, Thibaut Vaulet, Maarten Naesens, Claire Tinel, Baptiste Lamarthée   +16 more
wiley   +1 more source

A wearable artificial kidney for patients with end-stage renal disease. [PDF]

JCI Insight, 2016
Gura V, Rivara MB, Bieber S, Munshi R, Smith NC, Linke L, Kundzins J, Beizai M, Ezon C, Kessler L, Himmelfarb J.   +10 more
europepmc   +1 more source

Neural Information Processing and Time‐Series Prediction with Only Two Dynamical Memristors

Advanced Electronic Materials, EarlyView.
The present study demonstrates how simple circuits with only two memristive devices are utilized to perform high complexity temporal information processing tasks, like neural spike detection in noisy environment, or time‐series prediction. This circuit simplicity is enabled by the dynamical complexity of the memristive devices, i.e.
Dániel Molnár, Tímea Nóra Török, János Volk, Roland Kövecs, László Pósa, Péter Balázs, György Molnár, Nadia Jimenez Olalla, Zoltán Balogh, János Volk, Juerg Leuthold, Miklós Csontos, András Halbritter   +12 more
wiley   +1 more source

Artificial intelligence–based diagnosis of diabetic kidney disease using urinary VOC biosensor data [PDF]

Chatchai Kreepala, Watcharapong Anakkamatee, Anawin Pechbooranin   +2 more
openalex   +2 more sources

Revising Fascial Anatomy With a Focus on the Fusion Fascia in Mesenteric Gastrointestinal Cancer Surgery

Annals of Gastroenterological Surgery, EarlyView.
This review critically reassesses our prior hypothesis and proposes a revised anatomical model of the fusion fascia that is broadly applicable to GI cancer surgeries grounded in the principles of mesenteric resection. Our synthesis suggests that the fusion fascia is neither a dense connective tissue membrane nor a remnant of mesothelial fusion, but ...
Hisashi Shinohara, Yasunori Kurahashi, Jun Watanabe, Yuichi Nagakawa, Tatsuro Nakamura, Eiichiro Nakao, Yudai Hojo, Shugo Kohno, Motoki Murakami, Yoshinori Ishida   +9 more
wiley   +1 more source

ARTIFICIAL NEURAL NETWORKS AND LOGISTIC REGRESSION WITH AN ORDERED CATEGORICAL RESPONSE: STUDY CHRONIC KIDNEY DISEASE

, 2016
Mona Bary, Dina H. Abdel Hady, Zenab El Gamal, A Adepoju, M Adegbite, I Allen, C Seaman, M Catalogna, E Cohen, S Fishman, Z Halpern, U Nevo, E Ben-Jacob, J Chimka, H Wolfe, W Deng, W Chen, W Pei, P Dey, A Lamba, S Kumari, N Marwaha, E Elveren, N Yumuak, O Er, F Temurtas, A Tanrkulu, Kevin Fox, Rhonda Henning, Jonathan Reed, P Fedor, I Malenovsky, J Vanhara, W Sierka, J Havel, J Fernandez De Canete, S Gonzalez-Perez, J Ramos-Diaz, T Gregoire, B Driver, T Hastie, J Botha, C Schnitzler, J Havel, E Pea, A Rojas-Hernndez, J Doucet, A Panaye, S Jamieson, M Karlaftis, E Vlahogianni, T Knapp, L Mayer, V Michalkova, A Valigurova, M Dindo, J Vanhara, N Murarikova, J Vanhara, A Tothova, J Havel, National Kidney, Foundation, M Paliwal, U Kumar, Paulo Lisboa, F Azzam, Taktak, M Penedo, M Carreira, A Mosquera, D Cabello, B Galdn, E Rodrguez, J Pen-Mndez, Rodrguez Havel, Rodrguez, C Romero, Daz, P Velleman, W Leland, H White   +81 more
openalex   +1 more source

AI‐Enhanced Surface‐Enhanced Raman Scattering for Accurate and Sensitive Biomedical Sensing

Advanced Intelligent Discovery, EarlyView.
AI‐SERS advances spectral interpretation with greater precision and speed, enhancing molecular detection, biomedical analysis, and imaging. This review explores its essential contributions to biofluid analysis, disease identification, therapeutic agent evaluation, and high‐resolution biomedical imaging, aiding diagnostic decision‐making.
Seungki Lee, Rowoon Park, Ho Sang Jung
wiley   +1 more source