Results 111 to 120 of about 522,455 (311)

Remote Assessment of Ataxia Severity in SCA3 Across Multiple Centers and Time Points

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Spinocerebellar ataxia type 3 (SCA3) is a genetically defined ataxia. The Scale for Assessment and Rating of Ataxia (SARA) is a clinician‐reported outcome that measures ataxia severity at a single time point. In its standard application, SARA fails to capture short‐term fluctuations, limiting its sensitivity in trials.
Marcus Grobe‐Einsler, Vivian Maas, Arian Taheri Amin, Jennifer Faber, Tamara Schaprian, Katharina Hill, Matthis Synofzik, Lisa H. Graf, Heike Jacobi, Manuela Lima, Ana F. Ferreira, Bart P. van de Warrenburg, Ilse H. J. Willemse, Dagmar Timmann, Andreas Thieme, Paola Giunti, Hector Garcia‐Moreno, Magda M. Santana, Jeannette Hübener‐Schmid, Elin H. Davies, Thomas Klockgether   +20 more
wiley   +1 more source

Universal machine learning potentials under pressure

Journal of Physics: Materials
Abstract Universal machine learning interatomic potentials (uMLIPs) represent arguably the most successful application of machine learning to materials science, demonstrating remarkable performance across diverse applications. However, critical blind spots in their reliability persist.
Antoine Loew, Jonathan Schmidt, Silvana Botti, Miguel A L Marques   +3 more
openaire   +2 more sources

Clustering Algorithm Reveals Dopamine‐Motor Mismatch in Cognitively Preserved Parkinson's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To explore the relationship between dopaminergic denervation and motor impairment in two de novo Parkinson's disease (PD) cohorts. Methods n = 249 PD patients from Parkinson's Progression Markers Initiative (PPMI) and n = 84 from an external clinical cohort.
Rachele Malito, Chiara Meneghini, Alice Galli, Luca Gallo, Pierfrancesco Mitrotti, Paola Dimartino, Marianna Inglese, Cinzia Zatti, Alessandro Lupini, Andrea Pilotto, Alessandro Padovani, Micol Avenali, Enza Maria Valente, Cristina Tassorelli, Silvia P. Caminiti   +14 more
wiley   +1 more source

Introduction to machine learning potentials for atomistic simulations

Journal of Physics: Condensed Matter
Abstract Machine learning potentials have revolutionised the field of atomistic simulations in recent years and are becoming a mainstay in the toolbox of computational scientists. This paper aims to provide an overview and introduction into machine learning potentials and their practical application to scientific problems.
Fabian L Thiemann, Niamh O’Neill, Venkat Kapil, Angelos Michaelides, Christoph Schran   +4 more
openaire   +4 more sources

When not to use machine learning: A perspective on potential and limitations

MRS Bulletin, 2022
Abstract The unparalleled success of artificial intelligence (AI) in the technology sector has catalyzed an enormous amount of research in the scientific community. It has proven to be a powerful tool, but as with any rapidly developing field, the deluge of information can be overwhelming, confusing, and sometimes ...
openaire   +2 more sources

Strategies to Enrich Electrochemical Sensing Data with Analytical Relevance for Machine Learning Applications: A Focused Review

Sensors
In this review, recent advances regarding the integration of machine learning into electrochemical analysis are overviewed, focusing on the strategies to increase the analytical context of electrochemical data for enhanced machine learning applications ...
Mijeong Kang, Donghyeon Kim, Jihee Kim, Nakyung Kim, Seunghun Lee   +4 more
doaj   +1 more source

Review of Machine Unlearning [PDF]

Jisuanji kexue yu tansuo
To effectively protect data privacy and implement the “right to be forgotten”, it is necessary to eliminate the influence of specific subsets of training data from machine learning models and ensure that these data cannot be reverse-engineered.
HE Lisong, YANG Yang
doaj   +1 more source

Functional and Structural Evidence of Neurofluid Circuit Aberrations in Huntington Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Disrupted neurofluid regulation may contribute to neurodegeneration in Huntington disease (HD). Because neurofluid pathways influence waste clearance, inflammation, and the distribution of central nervous system (CNS)–delivered therapeutics, understanding their dysfunction is increasingly important as targeted treatments emerge.
Kilian Hett, Abigail Dubois, Melanie Leguizamon, Alexander Song, Paula Trujillo, Colin D. McKnight, Ciaran M. Considine, Manus J. Donahue, Daniel O. Claassen   +8 more
wiley   +1 more source

A Machine Learning Framework for Olive Farms Profit Prediction

, 2021
Agricultural systems are constantly stressed due to higher demands for products. Consequently, water resources consumed on irrigation are increased. In combination with the climatic change, those are major obstacles to maintaining sustainable development,
Mariana Mocanu, Panagiotis Christias
core   +1 more source

A Depolarizing Leak in Sodium Bicarbonate Cotransporter NBCe1 Causes Brain Edema

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives SLC4A4 encodes electrogenic sodium bicarbonate cotransporter NBCe1, prominently expressed in kidney and brain. Recessive loss‐of‐function variants in SLC4A4 cause proximal renal tubular acidosis, no brain edema. In the brain, NBCe1 is expressed by astrocytes, where it regulates pH and mediates astrocyte volume changes.
Quinty Bisseling, Mark D. Parker, Sven Kerst, Richard A. Pasternack, Jacob Tondreau, Marjolein Breur, Gemma M. van Rooijen‐van Leeuwen, Davide Tonduti, Ettore Salsano, Alejandra Darling, Joanna A. E. van Wijk, Susanna Törnroth‐Horsefield, Marianna Bugiani, Petra J. W. Pouwels, Quinten Waisfisz, Marjo S. van der Knaap, Rogier Min   +16 more
wiley   +1 more source