Results 161 to 170 of about 14,065,891 (304)

Which lecturers' characteristics facilitate the learning process? A qualitative study on students' perceptions in the rehabilitation sciences. [PDF]

BMC Med Educ, 2023
Battista S, Furri L, Pellegrini V, Giardulli B, Coppola I, Testa M, Dell'Isola A.   +6 more
europepmc   +1 more source

Predictive Value of Composite Inflammatory Markers for Stroke Prognosis: A Prospective Cohort Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Novel composite inflammatory markers' role in stroke prognosis is understudied, and the best predictor is unclear, requiring further exploration. Objectives This study aimed to systematically evaluate the associations of 6 novel composite inflammatory markers on stroke prognosis.
Bing Wu, Jie‐Jie Li, Jing Jing, Jin‐Xi Lin, Xia Meng, Yong Jiang, Yong‐Jun Wang, Hong‐Qiu Gu   +7 more
wiley   +1 more source

Collect a Holiday at The Idea Workshop

, 1975
Advertisement for books, kits, and other educational products Learning About ...
Learning About Learning
core   +1 more source

Enhancing Medical Education: The Role of Artificial Intelligence Tools in the Teaching-Learning Process. [PDF]

Adv Med Educ Pract
Kalhori Z, Bajoulvand R, Zahedian M, Malgard S, Aalaa M, Asadzandi S.   +5 more
europepmc   +1 more source

The Beginner Laparoscopists Trends in the Learning Process of Laparoscopy for Adnexal Gynecological Pathologies-The Experience of Our Center. [PDF]

Healthcare (Basel), 2023
Sima RM, Crăițan AV, Pleș L, Bobircă F, Amza M, Gorecki GP, Georgescu MT, Hamoud BH.   +7 more
europepmc   +1 more source

Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif, Diane Demailly, Gabriella A. Horvàth, Juan Dario Ortigoza Escobar, Nathalie Dorison, Mayté Castro Jiménez, Cécile A. Hubsch, Thomas Wirth, Gun‐Marie Hariz, Sophie Huby, Morgan Dornadic, Zohra Souei, Muhammad Mushhood Ur Rehman, Simone Hemm, Mehdi Boulaymen, Eduardo M. Moraud, Jocelyne Bloch, Xavier Vasques   +17 more
wiley   +1 more source

Targeted Active Learning for Bayesian Decision-Making

Active learning is usually applied to acquire labels of informative data points in supervised learning, to maximize accuracy in a sample-efficient way.
Kaski, Samuel, Tiulpin, Aleksei, Filstroff, Louis, Sundin, Iiris, Kylmäoja, Juuso, Mikkola, Petrus   +5 more
core  

Reinforcement Learning-Based Nonlinear Model Predictive Controller for a Jacketed Reactor: A Machine Learning Concept Validation Using Jetson Orin

ACS Omega
Aishwarya Selvamurugan, Aromal Vinod Kumar, Hrishikesh R. Palan, Arockiaraj Simiyon, Thirunavukkarasu Indiran   +4 more
doaj   +1 more source

Narratives of recovery from persistent fatigue: a stepwise learning process. [PDF]

Scand J Prim Health Care
Linnros H, Andreasson A, Norlin AK, Hydén LC.   +3 more
europepmc   +1 more source

Looking beyond the COVID-19 pandemic: the recalibration of student-teacher relationships in teaching and learning process. [PDF]

Med Educ Online, 2023
Soemantri D, Findyartini A, Mustika R, Felaza E, Arsyaf MA, Alfandy BP, Greviana N.   +6 more
europepmc   +1 more source