Results 231 to 240 of about 502,131 (289)

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

Research on the influence of personalized principles in AR educational resources on the learning effectiveness of college students. [PDF]

Front Psychol
Zeng J, Fan D, Hu H, Huang G, Zhang H.
europepmc   +1 more source

Personalized Federated Learning with Hierarchical Two-Branch Aggregation for Few-Shot Scenarios. [PDF]

Sensors (Basel)
Miao Y, Zhang W, Wang Y, Liu Y, Zhang Z, Meng L, Zhang B.   +6 more
europepmc   +1 more source

The application of artificial intelligence in the design of highly compatible knee prostheses: a systematic review. [PDF]

BMC Musculoskelet Disord
Li K, Zhang T, Wang X, Li F, Tian H.
europepmc   +1 more source

Personalized multi-agent reinforcement learning framework for adaptive chronic disease therapy management. [PDF]

Sci Rep
Ahmad F, AlGhamdi R.
europepmc   +1 more source

Artificial intelligence-driven personalized dietary recommendations for gastric cancer high-risk populations: a narrative review. [PDF]

Front Nutr
Chen J, Sun T, Zhang J, Huang J, Chen T, Weng Y, Xiang H, Dong Z, Huang Z, Cai X, Liang C, Zhang M, Yu W.   +12 more
europepmc   +1 more source

Editorial: Multi-modal learning with large-scale models. [PDF]

Front Neurorobot
Wang X, Li J.
europepmc   +1 more source

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Personalized Learning

EdTechnica, 2023
Personalized learning is an instructional strategy that tailors instruction to learners’ unique backgrounds, interests, abilities, or needs, and commonly includes the prescription that learners have some voice and choice (i.e., agency) in such tailoring.
Simon Cheung, Fu Wang, Lam Kwok, Petra Poulová   +3 more
openaire   +2 more sources

Personalized learning

2016 IEEE Global Engineering Education Conference (EDUCON), 2016
We address the personalized/customized learning claim made by proponents of game-based learning (GBL), that is, GBL supports effectively learning personalization. Even though popular and fascinating, this claim remains unfounded. Indeed, in the literature on games, mentions of the multiplicity of exploration paths are put forth as examples giving ...
Boumediene Belkhouche, Heba Ismail
openaire   +2 more sources

Personalized Learning

2020
This chapter is designed to inform teachers, administrators, policymakers, and researchers on the history of personalized learning (PL), the definition of personalized learning, and how it differentiates from other teaching strategies such as individualized, blended, differentiated, and adaptive.
openaire   +2 more sources