Results 141 to 150 of about 6,230,792 (401)

NIH Initiative to Improve Understanding of the Pancreas, Islet, and Autoimmunity in Type 1 Diabetes: The Human Pancreas Analysis Program (HPAP) [PDF]

, 2019
Klaus H. Kaestner, Alvin C. Powers, Ali Naji, Mark A. Atkinson   +3 more
openalex   +1 more source

The Case of a 28‐Year‐Old Woman With Medically Refractory Focal Epilepsy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT We present the case of a 28‐year‐old right‐handed woman with medically refractory focal epilepsy. Her seizure semiology and electroencephalography (EEG) indicated a seizure onset zone in the right central‐parietal area. However, both MRI and PET scans were unremarkable, showing no focal lesions or areas of altered metabolism.
Rishi Sharma, Ilo Leppik, Thomas Henry, Thaddeus Walczak, Sima Patel, Robert McGovern   +5 more
wiley   +1 more source

Use and perception of telemedicine in people with type 1 diabetes during the COVID‐19 pandemic—Results of a global survey [PDF]

, 2020
Sam N. Scott, Federico Y. Fontana, Thomas Züger, Markus Laimer, Christoph Stettler   +4 more
openalex   +1 more source

Semaglutide and Cardiovascular Outcomes in Patients with Type 2 Diabetes.

New England Journal of Medicine, 2016
S. Marso, S. Bain, A. Consoli, F. Eliaschewitz, E. Jódar, Lawrence A Leiter, I. Lingvay, J. Rosenstock, J. Seufert, M. Warren, V. Woo, O. Hansen, A. Holst, Jonas Pettersson, T. Vilsbøll   +14 more
semanticscholar   +1 more source

Deep Learning–Assisted Differentiation of Four Peripheral Neuropathies Using Corneal Confocal Microscopy

Annals of Clinical and Translational Neurology, EarlyView.
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, Ioannis N. Petropoulos, Mark Stettner, Maryam Ferdousi, Uazman Alam, Nathan Efron, Ahmed Serag, Rayaz A. Malik   +7 more
wiley   +1 more source

Arterial Calcification in Diabetes Mellitus [PDF]

, 2016
John N. Stabley, Dwight A. Towler
openalex   +1 more source

Assessing temporal differences in the predictive power of baseline TyG-related parameters for future diabetes: an analysis using time-dependent receiver operating characteristics [PDF]

, 2023
Maobin Kuang, Ruijuan Yang, Xin Huang, Chao Wang, Guotai Sheng, Guobo Xie, Yang Zou   +6 more
openalex   +1 more source

Liraglutide and Cardiovascular Outcomes in Type 2 Diabetes.

New England Journal of Medicine, 2016
S. Marso, Gilbert H. Daniels, Kirstine Brown-Frandsen, Peter Kristensen, Johannes F. E. Mann, Michael A Nauck, Steven E Nissen, Stuart Pocock, Neil R Poulter, Lasse S Ravn, William M Steinberg, Mette Stockner, B. Zinman, R. Bergenstal, J. B. Buse   +14 more
semanticscholar   +1 more source

The McCance Brain Care Score and Mortality: Evidence From a Large‐Scale Population‐Based Cohort

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives This study aimed to examine the relationship between the McCance Brain Care Score (BCS) and mortality in the general population. Methods We conducted a prospective, population‐based cohort study using data from the UK Biobank. Participants with complete data enabling calculation of BCS and full mortality information were included ...
Zhiqiang Xu, Xiaoxiao Wang, Nan Li
wiley   +1 more source

The Predictive Value of miR-16, -29a and -134 for Early Identification of Gestational Diabetes: A Nested Analysis of the DALI Cohort [PDF]

, 2021
Anja E. Sørensen, Mireille N. M. van Poppel, Gernot Desoyé, Peter Damm, David Simmons, Dorte Møller Jensen, Louise T. Dalgaard   +6 more
openalex   +1 more source