Results 191 to 200 of about 149,771 (261)

Target configuration determines how and what we learn during sensorimotor adaptation. [PDF]

NPJ Sci Learn
Villavicencio P, Tsay JS, de la Malla C.
europepmc   +1 more source

Bioprinting Organs—Science or Fiction?—A Review From Students to Students

Advanced Healthcare Materials, EarlyView.
Bioprinting artificial organs has the potential to revolutionize the medical field. This is a comprehensive review of the bioprinting workflow delving into the latest advancements in bioinks, materials and bioprinting techniques, exploring the critical stages of tissue maturation and functionality.
Nicoletta Murenu, Camilla Mussoni, Mateo S. Andrade Mier, Paula Buettner, Nathaly Chicaiza‐Cabezas, Yi‐Yu Robin Dai, Jessica Faber, Maren Fiedler, Zan Lamberger, Xuen Jen Ng, Vanessa Moessler, Anna Rederer, Jonas Roeder, Sabrina Stecher, Katinka Theis, Jeanette Weigelt, Silvia Budday, Gregor Lang, Natascha Schaefer   +18 more
wiley   +1 more source

Sequential gait interventions reveal non-reciprocal transfer between instructional and sensorimotor adaptation mechanisms. [PDF]

Sci Rep
Hoque A, Kim SH, Reed KB.
europepmc   +1 more source

Precise Control of Drug Release in Machine Learning‐Designed Antibody‐Eluting Implants for Postoperative Scarring Inhibition in Glaucoma

Advanced Healthcare Materials, EarlyView.
We developed a micro‐sized, biocompatible implant for postoperative sustained delivery of anti‐fibrotic antibodies in glaucoma surgery. Machine learning‐guided optimization of polymer composition, implant geometry, and porosity enabled precise control of drug release.
Mengqi Qin, Wenbing Jiang, Kai Xin Thong, Zeynep Ulker, Brihitejas Patel, Cynthia Yu‐Wai‐Man   +5 more
wiley   +1 more source

Computational Modeling Meets 3D Bioprinting: Emerging Synergies in Cardiovascular Disease Modeling

Advanced Healthcare Materials, EarlyView.
Emerging advances in three‐dimensional bioprinting and computational modeling are reshaping cardiovascular (CV) research by enabling more realistic, patient‐specific tissue platforms. This review surveys cutting‐edge approaches that merge biomimetic CV constructs with computational simulations to overcome the limitations of traditional models, improve ...
Tanmay Mukherjee, Mehdi Salar Amoli, Sarah Rezapourdamanab, Lama Rita El Shammas, Martin L. Tomov, Emilio A. Mendiola, Vahid Serpooshan, Reza Avazmohammadi   +7 more
wiley   +1 more source

Positive-Unlabeled Learning in Implicit Feedback from Data Missing-Not-At-Random Perspective. [PDF]

Entropy (Basel)
Wang S, Xia T, Yang L.
europepmc   +1 more source

Laser‐Assisted Processing and Modification of Bioactive Glasses: A Review

Advanced Healthcare Materials, EarlyView.
Laser technologies provide powerful tools to process and transform bioactive glasses for advanced biomedical applications. This review discusses laser‐matter interaction mechanisms, laser surface engineering, and laser‐assisted fabrication of scaffolds and nanofibers.
Antonio Riveiro, Mario González‐Quintas, Mónica Fernández‐Arias, Jesús del Val, Félix Quintero, Rafael Comesaña, Fernando Lusquiños, Julian R. Jones, Juan Pou   +8 more
wiley   +1 more source

A methodology for integrating AI into embodied human intelligence for the performance of complex tasks. [PDF]

Front Artif Intell
Ahmed T, Rikakis T.
europepmc   +1 more source

Smart Catheters for Diagnosis, Monitoring, and Therapy

Advanced Healthcare Materials, EarlyView.
This study presents a comprehensive review of smart catheters, an emerging class of medical devices that integrate embedded sensors, robotics, and communication systems, offering increased functionality and complexity to enable real‐time health monitoring, diagnostics, and treatment. Abstract This review explores smart catheters as an emerging class of
Azra Yaprak Tarman, Samiha Ahmed, Majed Othman Althumayri, Megan Guy, Darlenne Chavez Lugo, Frances S. Ligler, George T. Ligler, Rahmi Oklu, Hiroshi Kawahira, Michael J. McShane, Jun Kameoka, Jonathan Bova, Hatice Ceylan Koydemir   +12 more
wiley   +1 more source

No-rank tensor decomposition via metric learning. [PDF]

Sci Rep
Bagherian M.
europepmc   +1 more source