Results 161 to 170 of about 476,790 (313)

Dutch infants’ sensitivity to lexical tones under perceptual reorganization : a cross-sectional study

, 2011
Previous studies show that infants undergo a perceptual reorganization (PR) in their sensitivity to lexical tones between 6 and 9 months in the first year of life [Mattock & Burnham, 1; Mattock, Molnar, Polka & Burnham, 2].
Kager, René, Liu, Liquan (R18335)
core  

Early Clinical, Imaging, and Pathological Characteristics of SRPK3/TTN‐Digenic Myopathy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective SRPK3/TTN‐digenic myopathy was recently established as a skeletal muscle myopathy caused by digenic inheritance. This study characterizes the early clinical presentation of SRPK3/TTN‐digenic myopathy in one previously reported and seven newly identified pediatric patients.
Rotem Orbach, Sandra Donkervoort, Carola Hedberg‐Oldfors, Giovanni Baranello, Dimah Saade, Precilla D'Souza, Ruchee Patel, Eva Michael, A. Reghan Foley, Diana Bharucha‐Goebel, S. Jin Haugland, Meghan McAnally, Omer Abdul Hamid, Katherine Chao, Ellen F. Macnamara, Alan H. Beggs, Anna Sarkozy, Juliane Mueller, Steven A. Moore, Richard S. Finkel, Cynthia J. Tifft, Francesco Muntoni, Anders Oldfors, Carsten G. Bönnemann   +23 more
wiley   +1 more source

Kalman contrastive unsupervised representation learning

Scientific Reports
We first propose a Kalman contrastive (KalCo) framework for unsupervised representation learning by dictionary lookup. It builds a dynamic dictionary of encoded representation keys with a queue and a Kalman filter encoder, to which the encoded queries ...
Mohammad Mahdi Jahani Yekta
doaj   +1 more source

Advancements in Medical Radiology Through Multimodal Machine Learning: A Comprehensive Overview

Bioengineering
The majority of data collected and obtained from various sources over a patient’s lifetime can be assumed to comprise pertinent information for delivering the best possible treatment.
Imran Ul Haq, Mustafa Mhamed, Mohammed Al-Harbi, Hamid Osman, Zuhal Y. Hamd, Zhe Liu   +5 more
doaj   +1 more source

Simplified Temporal Consistency Reinforcement Learning

, 2023
Reinforcement learning (RL) is able to solve complex sequential decision-making tasks but is currently limited by sample efficiency and required computation.
Pajarinen, Joni, Zhao, Yi, Zhao, Wenshuai, Boney, Rinu, Kannala, Juho   +4 more
core  

Spatial and Volumetric Characteristics of Glioblastoma: Associations With Clinical Presentation and Survival

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective We aim to comprehensively analyze how regional tumor and edema characteristics are associated with clinical presentations and survival outcomes in a large cohort of glioblastoma patients. Methods Patients with IDH‐wildtype glioblastoma who received brain MRI from 2010 to 2023 were included.
Daniel J. Zhou, Marc Jaskir, Julian Gal, Yombe Fonkeu, Christos Davatzikos, MacLean P. Nasrallah, Jose Garcia, Rubo Xing, Stephen J. Bagley, Arati Desai, Richard E. Phillips, Steven Tobochnik, Colin A. Ellis, James J. Gugger, Nishant Sinha, Joel M. Stein, Kathryn A. Davis   +16 more
wiley   +1 more source

Scale Is Not All You Need: Revisiting the Biomimetic Roots of Deep Learning to Overcome Fundamental Limitations

IEEE Access
Deep Learning has historically drawn direct inspiration from nature, with Artificial Neural Networks initially grounded in neurobiological principles.
Malek Wahidi, Anthony Rizk, Rodrigue Imad   +2 more
doaj   +1 more source

Screening Routine Clinical Notes for Epilepsy Surgery Candidates Using Large Language Models

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Epilepsy surgery is severely underutilized despite proven efficacy, with substantial under‐referral of eligible patients in routine clinical practice. This study evaluated the potential role of large language models (LLMs) as decision‐support tools for screening unstructured clinical notes to identify epilepsy surgery candidates and ...
Uriel Fennig, Nadav Amir, Maya Schiller, Roni Loebenstein, Johnatan Nissan, Marina Boxer, Shany Guly Gofrit, Gal Goshen, Sándor Beniczky, Nicola Maggio   +9 more
wiley   +1 more source

Learning Efficient Representations for Reinforcement Learning

CoRR, 2015
Markov decision processes (MDPs) are a well studied framework for solving sequential decision making problems under uncertainty. Exact methods for solving MDPs based on dynamic programming such as policy iteration and value iteration are effective on small problems.
openaire   +2 more sources

Scalable and Efficient Protein Secondary Structure Prediction Using Autoencoder-Reduced ProtBERT Embeddings

Applied Sciences
This study proposes a deep learning framework for Protein Secondary Structure Prediction (PSSP) that prioritizes computational efficiency while preserving classification accuracy.
Yahya Najib Hamood Al-Shameri, İrfan Kösesoy, Hakan Gündüz, Ömer Faruk Yılmaz   +3 more
doaj   +1 more source