Results 211 to 220 of about 4,022,746 (290)

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

Editorial for the Special Issue "Molecular Biology in Drug Design and Precision Therapy". [PDF]

Curr Issues Mol Biol
Drăgoi CM, Dumitrescu IB, Nicolae AC.
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

The juji-gatame technique can be used in the special judo fitness test to evaluate fitness condition in grappling fighters: A crossover trial. [PDF]

Medicine (Baltimore)
de Almeida-Neto PF, Bulhões-Correia A, de Assis GG, Ceylan Hİ, Rocha RFC, Medeiros da Silva I, Gomes da Silva JC, Silva Dantas PM, Stefanica V, Cabral BGAT.   +9 more
europepmc   +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

Current issue on special topic: robotic single-port system in general surgery. [PDF]

Ann Surg Treat Res
Kim DW.
europepmc   +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

Olink Proteomics Analysis Reveals Heterogeneous Responses to FcRn Blockade in Anti‐AChR Antibody‐Positive Myasthenia Gravis: FGF‐19 as a Novel Biomarker

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective This study aimed to systematically observe the clinical manifestations, immune cell subsets, and dynamic changes in serological indicators in patients with myasthenia gravis (MG) before and after efgartigimod (EFG) treatment. Methods We analyzed the baseline data, laboratory parameters, and lymphocyte subset proportions in MG ...
Tiancheng Luo, Deyou Peng, Zhouao Zhang, Mingjin Yang, Xinyan Guo, Tianyu Ma, Xiaoyu Huang, Mingming Xu, Linlin Fu, Yong Zhang   +9 more
wiley   +1 more source

3D Patellar instability Anatomical Severity Score (3D-PASS): A Novel Machine Learning Score Using 3D Bone Position From MRI to Predict Outcomes of Patellar Instability Treatment (Using a Subset of Data in the JUPITER Cohort). [PDF]

Orthop J Sports Med
Sinopoli ML, Gatti AA, Wright CE, Bartsch A, Veerkamp MW, Boutin RD, Mintz DN, Emery KH, Shea KG, Chaudhari AS, JUPITER Study Group, Wall EJ, Elangovan S, Green DW, Fabricant PD, Strickland SM, Shubin Stein BE, Parikh SN, Delp SL, Sherman SL.   +19 more
europepmc   +1 more source