Results 241 to 250 of about 1,522,732 (367)

Comparative study of different worldwide versions of the thyroid risk stratification system in patients with thyroid nodules in China. [PDF]

Quant Imaging Med Surg
Wang JJ, Huang HQ, Zheng RT, Lin ZH, Wu MM, Cai SZ, Liao XY, Guo DM, Chen Z.   +8 more
europepmc   +1 more source

Prediction of Myasthenia Gravis Worsening: A Machine Learning Algorithm Using Wearables and Patient‐Reported Measures

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Myasthenia gravis (MG) is a rare disorder characterized by fluctuating muscle weakness with potential life‐threatening crises. Timely interventions may be delayed by limited access to care and fragmented documentation. Our objective was to develop predictive algorithms for MG deterioration using multimodal telemedicine data ...
Maike Stein, Haoqi Sun, Sophie Lehnerer, Lea Gerischer, Maximilian Mönch, Christian Meisel, Andreas Meisel, Pushpa Narayanaswami   +7 more
wiley   +1 more source

Risk Stratification for Patients in Cardiogenic Shock After Acute Myocardial Infarction.

Journal of the American College of Cardiology, 2017
Janine Pöss, J. Köster, G. Fuernau, I. Eitel, S. de Waha, T. Ouarrak, Johan Lassus, V. Harjola, U. Zeymer, H. Thiele, S. Desch   +10 more
semanticscholar   +1 more source

Chronological and Spatial Distribution of Skeletal Muscle Fat Replacement in FHL1‐Related Myopathies

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives Variants in the FHL1 gene cause FHL1‐related myopathies (FHL1‐RMs), a group of neuromuscular disorders with diverse clinical presentations. This study aimed to comprehensively characterize the spatial and temporal patterns of skeletal muscle fat replacement throughout the whole body in FHL1‐RMs, to examine disease progression over ...
Rui Shimazaki, Satoru Noguchi, Hotake Takizawa, Yasushi Oya, Yuji Takahashi, Hirofumi Komaki, Hajime Arahata, Shinichiro Hayashi, Ichizo Nishino   +8 more
wiley   +1 more source

Comprehensive Pediatric Health Risk Stratification Using an AI-Driven Framework in Children Aged 2 to 8 Years: Design and Validation Study.

JMIR Med Inform
Mao Z, Chen J.
europepmc   +1 more source

Artificial Intelligence-Enabled Electrocardiogram for the Detection and Management of Cancer Therapy-Related Cardiotoxicity. [PDF]

Cancer Innov
Song W, Gao R, Liu T.
europepmc   +1 more source

Is thyroid imaging reporting and data system useful as an adult ultrasonographic malignancy risk stratification method in pediatric thyroid nodules?

, 2019
YaseminDurum Polat, Veli Süha Öztürk, Nimet Ersoz, Ahmet Anık, CanZafer Karaman   +4 more
openalex   +1 more source

Neuroblastoma: clinical and biological approach to risk stratification and treatment

Cell and Tissue Research, 2018
Vanessa P. Tolbert, K. Matthay
semanticscholar   +1 more source

Use of Symptomatic Drug Treatment for Fatigue in Multiple Sclerosis and Patterns of Work Loss

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To describe the use of central stimulants and amantadine for fatigue in MS and evaluate a potential association with reduced work loss in people with MS. Methods We conducted a nationwide, matched, register‐based cohort study in Sweden (2006 to 2023) using national registers with prospective data collection.
Simon Englund, Johan Reutfors, Thomas Frisell, Fredrik Piehl   +3 more
wiley   +1 more source

Comparative Diagnostic Performance of Ultrasound-Based Risk Stratification Systems in Thyroid Nodule Evaluations by Otolaryngologists. [PDF]

Diagnostics (Basel)
Wu JY, Cheng PC, Wen MH, Chang CM, Lo WC, Cheng PW, Wu PH, Liao LJ.   +7 more
europepmc   +1 more source