Results 91 to 100 of about 414,443 (278)
This paper describes the motion control of hyper redundant robots using a learning control scheme based on linear combination of error history. The learning control scheme is formulated with three elements: general solution of inverse kinematics with ...
Daisuke MATSUURA, Nobuyuki IWATSUKI
doaj +1 more source
In this study, we developed a deep learning method for mitotic figure counting in H&E‐stained whole‐slide images and evaluated its prognostic impact in 13 external validation cohorts from seven different cancer types. Patients with more mitotic figures per mm2 had significantly worse patient outcome in all the studied cancer types except colorectal ...
Joakim Kalsnes +32 more
wiley +1 more source
The Aging Blood: Cellular Origins, Circulating Drivers, and Therapeutic Potential
As a conduit linking all organs, the blood system both reflects and actively drives systemic aging. This review highlights how circulating pro‐aging and antiaging factors and age‐associated hematopoietic stem cell dysfunction contribute to immunosenescence and multi‐organ decline, positioning the hematopoietic system as a target for aging intervention.
Hanqing He, Jianwei Wang
wiley +1 more source
Implementation of the Iterative Learning Control in feedback controlled systems [PDF]
Iterative Learning Control (ILC) is a data-driven control strategy designed for systems that continuously repeat their reference trajectories and operating conditions. For example, robotic systems in manufacturing often exhibit such behavior.
Matijević Milan S. +4 more
doaj +1 more source
ABSTRACT Objective Peripheral neuropathies contribute to patient disability but may be diagnosed late or missed altogether due to late referral, limitation of current diagnostic methods and lack of specialized testing facilities. To address this clinical gap, we developed NeuropathAI, an interpretable deep learning–based multiclass classification ...
Chaima Ben Rabah +7 more
wiley +1 more source
A Neural Network Model of Spatio-Temporal Pattern Recognition, Recall and Timing [PDF]
This paper describes the design of a self~organizing, hierarchical neural network model of unsupervised serial learning. The model learns to recognize, store, and recall sequences of unitized patterns, using either short-term memory (STM) or both STM and
Mannes, Christian
core +1 more source
ABSTRACT Background Myasthenia gravis (MG) is a rare disorder characterized by fluctuating muscle weakness with potential life‐threatening crises. Timely interventions may be delayed by limited access to care and fragmented documentation. Our objective was to develop predictive algorithms for MG deterioration using multimodal telemedicine data ...
Maike Stein +7 more
wiley +1 more source
Serial learning: A multilevel access analysis [PDF]
In Experiment I the lists were 36 and 48 unrelated words. Each was divided into successive groups of four words and learned to a perfect criterion. In Experiment II the lists were made up of six categorical groups of five exemplars each. Degree of learning was varied. In both experiments serial anticipation learning was followed by ordinary free recall
openaire +2 more sources
Lessons Learned From a Delayed‐Start Trial of Modafinil for Freezing of Gait in Parkinson's Disease
ABSTRACT Objective Freezing of gait (FOG) in people with Parkinson's disease (PwPD) is debilitating and has limited treatments. Modafinil modulates beta/gamma band activity in the pedunculopontine nucleus (PPN), like PPN deep brain stimulation. We therefore tested the hypothesis that Modafinil would improve FOG in PwPD.
Tuhin Virmani +8 more
wiley +1 more source
The Internationalization of Global Start-Ups: Understanding the Role of Serial Entrepreneurs [PDF]
Using qualitative methodology, we aim to understand how serial entrepreneurs can foster the development of born-global ventures. We consider a born-global start-up as the final stage of the learning process for a serial entrepreneur, advancing ...
Odorici Vincenza +2 more
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