Results 211 to 220 of about 157,751 (260)

New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design

Advanced Engineering Materials, EarlyView.
This work introduces an innovative framework for designing structured materials by ex panding the design space through reparameterization of qualitative variables into continuous structural descriptors. Combined with machine‐learning‐based prediction and multi‐objective optimization, the approach enables the discovery of novel lattice architectures ...
G. H. Gahimbare, Y. Beideler, D. Chune, R. De Guio, T. Roland, H. Chibane   +5 more
wiley   +1 more source

Differentially Expressed Gene Annotator (DEGAn): automated annotation and analysis of DEGs datasets with OS and PFS data. [PDF]

Bioinform Adv
Agapito G, Cannataro M.
europepmc   +1 more source

Psychological determinants of trust and reliance on automated decision-support systems: an integrated expectancy-based perspective. [PDF]

Front Psychol
Rehman U.
europepmc   +1 more source

A U-Net model for epidermal segmentation in optical coherence tomography images of actinic keratosis. [PDF]

PLoS One
Angelis T, Philipsen PA, Ortner VK, Fredman G, Haedersdal M, Untracht GR.   +5 more
europepmc   +1 more source

Machine learning assisted classification of periodontal health and periodontitis using alveolar bone loss measurements on bitewing radiographs. [PDF]

Front Oral Health
Yadadi SS, Shetty RM, Sowmya V, Bakie W, Jaziri K, Alsaraierh H, Hijazi HA, Reddy GS, Sudhakar S, Vinay V, Desai VB.   +10 more
europepmc   +1 more source

Toward Objective Wound Edge Classification in Clinical Practice. [PDF]

Exp Dermatol
Zengarini C, Giacometti T, Merli Y, Griffa D, Rapparini L, Natale A, Fruci M, Castellani G, Remondini D, La Placa M, Pileri A, Starace M, Curti N.   +12 more
europepmc   +1 more source

Automated PROMISE V2 Scoring from PSMA PET/CT Reports Using Large Language Models: A Comparative Evaluation of Prompt Design and Model Performance. [PDF]

Curr Oncol
Speicher T, Demirkol IE, Blickle A, Bastian MB, Maus S, Schaefer-Schuler A, Bartholomä M, Burgard C, Ezziddin S, Rosar F.   +9 more
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Elementary teachers’ perceptions of automated feedback and automated scoring: Transforming the teaching and learning of writing using automated writing evaluation

Computers and Education, 2021
Abstract The present study used a focus group methodology to qualitatively explore elementary writing teachers' attitudes and experiences using an automated writing evaluation (AWE) system called MI Write as part of a districtwide implementation of MI Write in Grades 3–5 in 14 elementary schools.
Joshua Wilson, Charles Macarthur
exaly   +2 more sources

ChatGPT for Automated Writing Evaluation in Scholarly Writing Instruction

Journal of Nursing Education, 2023
Background: Effective strategies for developing scholarly writing skills in postsecondary nursing students are needed. Generative artificial intelligence (GAI) tools, such as ChatGPT, for automated writing evaluation (AWE) hold promise for mitigating challenges associated with scholarly writing instruction in nursing education.
Jessica L, Parker, Kimberly, Becker, Catherine, Carroca   +2 more
openaire   +2 more sources

Towards context-aware automated writing evaluation systems [PDF]

Proceedings of the 1st ACM SIGSOFT International Workshop on Education through Advanced Software Engineering and Artificial Intelligence, 2019
Writing is a crucial skill in our society, which is regularly exerted by students across all disciplines. Automated essay scoring and automatic writing evaluation systems can support professors in the evaluation of written texts and, conversely, help students improving their writing.
Patout, Pierre-André, CORDY, Maxime
openaire   +2 more sources