Results 201 to 210 of about 1,238,639 (328)

Detection and Classification of Alzheimer's Disease Using Deep and Machine Learning. [PDF]

Tomography
Khalid MZ, Iqbal N, Ali B, Rahman JSU, Iqbal S, Almudaimeegh L, Hamd ZY, Gareeballah A.   +7 more
europepmc   +1 more source

Validation of the mjn-SERAS medical device for the early detection of epileptic seizures in refractory epilepsy patients in a normalised environment: Protocol for a prospective, multicentre, controlled and randomized, pilot clinical study (Preprint) [PDF]

David mjn-SERAS, Gustavo mjn-SERAS, Gustavo Torres‐Gaona, Asier Gómez‐Ibáñez, Arjune Sen, Bernhard J. Steinhoff, Ángel Aledo‐Serrano, Adrián Trejo, David Blánquez   +8 more
openalex   +1 more source

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

Impact of Asymptomatic Intracranial Hemorrhage on Outcome After Endovascular Stroke Treatment

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Endovascular treatment (EVT) achieves high rates of recanalization in acute large‐vessel occlusion (LVO) stroke, but functional recovery remains heterogeneous. While symptomatic intracranial hemorrhage (sICH) has been well studied, the prognostic impact of asymptomatic intracranial hemorrhage (aICH) after EVT is less certain ...
Shihai Yang, Chengsong Yue, Zhuang Li, Xiaolei Shi, Haoxuan Zhu, Jie Yang, Linyu Li, Jiaxing Song, Shitao Fan, Gaoming Li, Wenzhe Sun, Zhixian Ye, Jiacheng Huang, Dahong Yang, Jinfu Ma, Xu Xu, Zhixi Wang, Lilan Wang, Guojian Liu, Fengli Li, Changwei Guo, Li Qi, Wenjie Zi   +22 more
wiley   +1 more source

Ball bearing fault detection using an acoustic based machine learning approach. [PDF]

Sci Rep
Chandrakala CB, Karumanchi SS, Raghudathesh GP, Madhwesh N.   +3 more
europepmc   +1 more source

Early detection and Multistage classification of Diabetic Retinopathy using Random Forest Classifier [PDF]

, 2018
Deepthi K Prasad, L. Vibha, K R Venugopal   +2 more
openalex   +1 more source

Fluid Biomarkers of Disease Burden and Cognitive Dysfunction in Progressive Supranuclear Palsy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Identifying objective biomarkers for progressive supranuclear palsy (PSP) is crucial to improving diagnosis and establishing clinical trial and treatment endpoints. This study evaluated fluid biomarkers in PSP versus controls and their associations with regional 18F‐PI‐2620 tau‐PET, clinical, and cognitive outcomes.
Roxane Dilcher, Charles B. Malpas, Stuart J. McDonald, William T. O’Brien, Craig Despott, Kelly L. Bertram, Matthew P. Pase, Lukas Frontzkowski, Meng Law, Terence J. O’Brien, Lucy Vivash   +10 more
wiley   +1 more source

Optimizing Random Forest Models for Early Detection of Defects in Steel

Tri Surawan, Adhitio Satyo Bayangkari Karno, Widi Hastomo, Reza Fitriansyah, Ahmad Eko Saputro, Indra Bakti   +5 more
openalex   +2 more sources

Figure S4 from Estimating the Opportunity for Early Detection of Ovarian Cancer Using Individual-Patient Data from a Large Randomized Controlled Trial [PDF]

Marc D. Ryser, Shannon T. Holloway, Raphaël Morsomme, Andy Ryan, Sophia Apostolidou, Aleksandra Gentry‐Maharaj, Kemal Çag̃lar Gög̃ebakan, Jane Lange, Jason Xu, Usha Menon, Ruth Etzioni   +10 more
openalex   +1 more source

A Scoping Review on Artificial Intelligence–Supported Interventions for Nonpharmacologic Management of Chronic Rheumatic Diseases

Arthritis Care &Research, EarlyView.
This review summarizes artificial intelligence (AI)‐supported nonpharmacological interventions for adults with chronic rheumatic diseases, detailing their components, purpose, and current evidence base. We searched Embase, PubMed, Cochrane, and Scopus databases for studies describing AI‐supported interventions for adults with chronic rheumatic diseases.
Nirali Shah, Alexis Castellanos, Yen Chen, John Piette, Amy Bucher, Susan Murphy   +5 more
wiley   +1 more source