Results 171 to 180 of about 12,076,669 (306)

Clinical Validation of Artificial Intelligence (AI)‐based Cartilage Segmentation Predicting Knee Replacement

Arthritis Care &Research, Accepted Article.
Objective For cartilage morphology to serve as a scalable endpoint in clinical trials, analyses should be performed automatically without human interaction. To clinically validate artificial intelligence (AI)‐based analysis, we studied cartilage loss from MRI prior to knee replacement.
Felix Eckstein, David J. Hunter, C. Kent Kwoh, Wolfgang Wirth   +3 more
wiley   +1 more source

Human-machine interaction in optical polyp diagnosis: decision-making after CADx polyp diagnosis. [PDF]

J Can Assoc Gastroenterol
Dubois D, Jalal Y, Pohl H, Rex DK, Hassan C, Djinbachian R, Oleksiw M, Michal V, von Renteln D.   +8 more
europepmc   +1 more source

NFDI MatWerk Ontology (MWO): A BFO‐Compliant Ontology for Research Data Management in Materials Science and Engineering

Advanced Engineering Materials, EarlyView.
This article presents the NFDI‐MatWerk Ontology (MWO), a Basic Formal Ontology‐based framework for interoperable research data management in materials science and engineering (MSE). Covering consortium structures, research data management resources, services, and instruments, MWO enables semantic integration, Findable, Accessible, Interoperable, and ...
Hossein Beygi Nasrabadi, Ebrahim Norouzi, Kostiantyn Hubaiev, Jörg Waitelonis, Harald Sack   +4 more
wiley   +1 more source

Design of a mixed reality-based digital twin human-machine interaction system for special working conditions. [PDF]

Front Robot AI
Li S, Hu Y, Li H, Xu J, Li M, Zhang Y, Ren Q.   +6 more
europepmc   +1 more source

Field Report from Collaborative Research Center 1625: Heterogeneous Research Data Management Using Ontology Representations

Advanced Engineering Materials, EarlyView.
A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed, Samuel García Vázquez, Behnam Mardani, Victor Dudarev, Alfred Ludwig, Maribel Acosta, Markus Stricker   +6 more
wiley   +1 more source

A standardized personality lexicon for enhancing personalized human-machine interaction. [PDF]

Sci Data
Jin T, Cai H, Shi X, Kou X, Hu X, Zhong H, Yang Y, Jiang J, Li Y, Zhang W.   +9 more
europepmc   +1 more source

Editorial: Neurorobotics and strategies for adaptive human-machine interaction, volume II. [PDF]

Front Neurorobot, 2023
Cordella F, Soekadar SR, Zollo L.
europepmc   +1 more source

Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization

Advanced Engineering Materials, EarlyView.
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier, Moritz Blum, Luana Caron, Alisa Chirkova, Philipp Cimiano, Basil Ell, Inga Ennen, Michael Feige, Maik Gaerner, Thomas Hilbig, Andreas Hütten, Günter Reiss, Tapas Samanta, Sonja Schöning, Christian Schröder, Lennart Schwan, Chris Taake, Martin Wortmann   +17 more
wiley   +1 more source

Perceiving and predicting the intended motion with human-machine interaction force for walking assistive exoskeleton robot

, 2013
The characteristic of man in the loop has always brought lots of difficulties for the control of exoskeleton. To solve these, a hybrid control method based on human-machine interaction force (HMIF) is proposed and applied to the control of lower limb ...
Yang MY(杨明毅), Xu YL(徐永利), Xu ZG(徐志刚), Liu Y(刘勇), He Y(贺云)   +4 more
core  

Graphene Aerogel-Based Flexible Pressure Sensor for Physiological Signal Detection and Human-Machine Interaction. [PDF]

Nanomicro Lett
Wang Z, Zhao Z, Tu Q, Yao C, Liu Z, Zhou C, Xu L, Guo S, Meng C, Shao G, Cheng H, Yang L.   +11 more
europepmc   +1 more source