Results 191 to 200 of about 15,843,136 (243)

Clinical prediction models using machine learning in oncology: challenges and recommendations. [PDF]

BMJ Oncol
Collins GS, Chester-Jones M, Gerry S, Ma J, Matos J, Sehjal J, Tsegaye B, Dhiman P.   +7 more
europepmc   +1 more source

Comprehensive Assessment of Arterial, Tissue, and Venous Collaterals for Evaluating the Infarct Growth Rate: The Multimodal Collateral Score

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Collaterals are crucial factors that influence the infarct growth rate (IGR). We aimed to determine whether a comprehensive multimodal collateral score (MCS), incorporating collateral assessment at the arterial, tissue, and venous levels, is associated with functional independence and provides incremental prognostic value over ...
Giorgio Busto, Umberto Pensato, Ilaria Casetta, Giorgio U. Marcello, Angelo Barra, Anna Poggesi, Edoardo Carlesi, Sara Mancini, Andrea Ginestroni, Vittorio Miele, Alessandro Padovani, Andrea Morotti, Enrico Fainardi   +12 more
wiley   +1 more source

Editorial: Community series in novel reliable approaches for prediction and clinical decision-making in cancer, volume II

Frontiers in Immunology
Ines Zidi, Safa Bhar Layeb, Safa Bhar Layeb, Vera Rebmann   +3 more
doaj   +1 more source

A decomposition of Fisher's information to inform sample size for developing or updating fair and precise clinical prediction models - part 3: continuous outcomes. [PDF]

Diagn Progn Res
Whittle R, Riley RD, Archer L, Collins GS, Legha A, Snell KI, Ensor J.   +6 more
europepmc   +1 more source

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

Community medical centers struggle to produce well-calibrated clinical prediction models: Data augmentation can help. [PDF]

J Biomed Inform
Brown KE, Malin BA, Davis SE.
europepmc   +1 more source

Risk of Non‐Arteritic Anterior Ischemic Optic Neuropathy in Idiopathic Intracranial Hypertension Patients Treated with GLP‐1 Receptor Agonists

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Introduction Glucagon‐like peptide‐1 receptor agonists (GLP‐1 RAs) have demonstrated significant weight‐reducing effects and may offer benefits in idiopathic intracranial hypertension (IIH); however, recent concerns about the risk of non‐arteritic anterior ischemic optic neuropathy (NAION) have emerged.
Faisal A. Al‐Harbi, Mohanad A. Alkuwaiti, Yazeed B. Alaql, Ahmed K. Alsaif, Ahmed A. Alessa, Meshari Ayed Alharbi, Mohammed Alfalah, Saud A. Alnaaim, Sajjad M. AlHaddad, Ahmed Y. Azzam   +9 more
wiley   +1 more source

Resampling methods for class imbalance in clinical prediction models: A scoping review protocol. [PDF]

PLoS One
Abdelhay O, Shatnawi A, Najadat H, Altamimi T.   +3 more
europepmc   +1 more source

Comparative Effectiveness and Safety of Inebilizumab Versus Rituximab in AQP4‐IgG‐Positive NMOSD

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Rituximab (anti‐CD20, RTX) and inebilizumab (anti‐CD19, INE) represent B‐cell‐depleting therapies used for aquaporin‐4 antibody‐positive (AQP4‐IgG+) neuromyelitis optica spectrum disorder (NMOSD); however, direct comparative evidence remains limited.
Jie Lin, Binbin Xue, Dewei Xie, Jia Li, Juyuan Pan, Lanbing Zhu, Qiaowen Tong, Jing Lin, Ruofan Zhu, Xu Zhang, Junhui Xia, Xiang Li   +11 more
wiley   +1 more source

Monitoring strategies for continuous evaluation of deployed clinical prediction models. [PDF]

J Biomed Inform
Kim GYE, Corbin CK, Grolleau F, Baiocchi M, Chen JH.   +4 more
europepmc   +1 more source