Results 141 to 150 of about 88,634 (286)

Chronological Diagnostic Algorithm Predicting Neuropathology in Parkinsonism

Annals of Neurology, EarlyView.
Objective Pre‐mortem diagnosis of parkinsonism is often challenging due to atypical presentations, overlapping syndromes, and co‐pathologies. This study aimed to develop a machine learning‐based algorithm predicting neuropathology in parkinsonism using chronological clinical presentations, which has previously been underexplored.
Daisuke Ono, Hiroaki Sekiya, Alexia R. Maier, Neill R. Graff‐Radford, Zbigniew K. Wszolek, Dennis W. Dickson   +5 more
wiley   +1 more source

Use of Machine Learning to Identify Markers of Risk for Fragile X‐Associated Tremor/Ataxia Syndrome: A Preliminary Analysis

Annals of Neurology, EarlyView.
Objective The objective of this study was to examine whether machine learning has the capacity to prospectively identify and predict the emergence of Fragile X‐associated tremor/ataxia syndrome (FXTAS) among male fragile X premutation carriers (PCs). Methods We explored neuropsychological and motor evaluation metrics, brain magnetic resonance imaging ...
Chitrabhanu Gupta, Angeela Poudel, Jun Yi Wang, Randi Hagerman, Glenda Espinal, Jessica Famula, Andrea Schneider, Flora Tassone, Susan M. Rivera, Chen‐Nee Chuah, David Hessl   +10 more
wiley   +1 more source

Seitliche π‐Koordination einer C≡C‐Dreifachbindung an Technetium forciert durch den As,CC,As Alkin‐Pinzetten‐Liganden 1,2‐Bis(2‐(Diisopropylarsaneyl)‐4‐(Trifluormethyl)phenyl)Ethin

Angewandte Chemie, EarlyView.
Technetium‐Alkin‐Komplexe konnten jahrzehntelang nicht isoliert werden, obwohl es zahlreiche Berichte über benachbarte Elemente gab. Der einzige Hinweis auf ihre Existenz war die Isolierung von Vinylidencarbenen oder deren Folgeprodukten. Stabile, kristalline Tc(III)‐ und Tc(V)‐Alkin‐Komplexe (sowie deren Re‐Analoga) eines auf Tolan basierenden As,CC ...
Maximilian Roca Jungfer, Moritz Johannes Ernst, Lukas Eberle, Marius Kesselring, Guilhem Claude, Joachim Ballmann   +5 more
wiley   +1 more source

Prediction of Imminent Peritoneal Dialysis-Associated Peritonitis Using Time-Updated Electronic Health Records and Machine Learning: A Temporal Validation Study. [PDF]

J Inflamm Res
Wang Q, Luo Q, Ding Y, Wan S, Zhang Y, Xiong F.   +5 more
europepmc   +1 more source

Enhancing large language model clinical support information with machine learning risk and explainability: a feasibility study. [PDF]

Intensive Care Med Exp
Yeh YC, Yang HY, Chiu CT, Chao A, Chuang YC, Chan WS.   +5 more
europepmc   +1 more source

Auditing shortcut learning and misclassification in artificial intelligence-based breast cancer genomic subtyping. [PDF]

JAMIA Open
Borges J.
europepmc   +1 more source

Prediction of Properties of Polymer Composite Formulations Using Ensemble Models With Feature Generation

Journal of Applied Polymer Science, EarlyView.
This study develops an interpretable machine‐learning framework to predict multiple properties of polymer composites based on composition and processing variables. By combining ensemble models with composition‐based feature generation and SHAP‐based interpretation, the approach reveals composition‐property relationships and supports efficient multi ...
Dong Ryeol Shin, Sung Kwang Lee
wiley   +1 more source

SHAP-based explainable AI framework for autism severity classification using 3D motor biomarkers. [PDF]

Front Psychiatry
Fırat Y.
europepmc   +1 more source

Identifying Systemic Lupus Erythematosus From Serum Proteomic Profiles Using Machine Learning and Genetic Risk Stratification

Arthritis &Rheumatology, EarlyView.
Objective Proteome‐wide risk models for lupus remain underexplored. We developed classification models to identify lupus from serum proteomic profiles. Methods Patients with lupus and individuals with other autoimmune diseases in the UK Biobank were included.
Mehmet Hocaoǧlu, Jishnu Das, Amr H. Sawalha   +2 more
wiley   +1 more source

Explainable machine learning using urinary metabolomics to predict pediatric sepsis-associated acute kidney injury: a two-center prospective observational study. [PDF]

Ren Fail
Qian Y, Jiang Z, Miao H, Chu L, Zeng J, Fan M, Gu W, Wu M, Xu F, Ge X.   +9 more
europepmc   +1 more source