Results 51 to 60 of about 242,529 (275)

Overview of molecular signatures of senescence and associated resources: pros and cons

FEBS Open Bio, EarlyView.
Cells can enter a stress response state termed cellular senescence that is involved in various diseases and aging. Detecting these cells is challenging due to the lack of universal biomarkers. This review presents the current state of senescence identification, from biomarkers to molecular signatures, compares tools and approaches, and highlights ...
Orestis A. Ntintas, Sylvia Vagena, Pavlos Pantelis, Giorgos Theocharous, Russel Petty, Konstantinos Evangelou, Vassilis G. Gorgoulis   +6 more
wiley   +1 more source

Advancements in Semi-Supervised Deep Learning for Brain Tumor Segmentation in MRI: A Literature Review

AI
For automatic tumor segmentation in magnetic resonance imaging (MRI), deep learning offers very powerful technical support with significant results. However, the success of supervised learning is strongly dependent on the quantity and accuracy of labeled
Chengcheng Jin, Theam Foo Ng, Haidi Ibrahim   +2 more
doaj   +1 more source

An Efficient Approach to Select Instances in Self-Training and Co-Training Semi-Supervised Methods

IEEE Access, 2022
Semi-supervised learning is a machine learning approach that integrates supervised and unsupervised learning mechanisms. In this learning, most of labels in the training set are unknown, while there is a small part of data that has known labels. The semi-
Karliane Medeiros Ovidio Vale, Arthur Costa Gorgonio, Flavius Da Luz E Gorgonio, Anne Magaly De Paula Canuto   +3 more
doaj   +1 more source

Impact of a senior research thesis on students' perceptions of scientific inquiry in distinct student populations

FEBS Open Bio, EarlyView.
This study addressed how a senior research thesis is perceived by undergraduate students. It assessed students' perception of research skills, epistemological beliefs, and career goals in Biochemistry (science) and BDC (science‐business) students. Completing a thesis improved confidence in research skills, resilience, scientific identity, closed gender‐
Celeste Suart, Haley L. Zubyk, Michelle Ogrodnik, Caitlin E. Mullarkey, Felicia Vulcu   +4 more
wiley   +1 more source

Reducing Label Dependency in Human Activity Recognition with Wearables: From Supervised Learning to Novel Weakly Self-Supervised Approaches

Sensors
Human activity recognition (HAR) using wearable sensors has advanced through various machine learning paradigms, each with inherent trade-offs between performance and labeling requirements.
Taoran Sheng, Manfred Huber
doaj   +1 more source

CSF Levels of NPTX2 Are Associated With Less Brain Atrophy Over Time in Cognitively Unimpaired Individuals

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Introduction Neuronal pentraxin 2 (NPTX2) is a synaptic protein involved in synaptic plasticity and regulation of neuronal excitability. Lower baseline cerebrospinal fluid (CSF) NPTX2 levels have been shown to be associated with an earlier onset of mild cognitive impairment (MCI), a pre‐dementia syndrome, even after CSF Alzheimer's Disease (AD)
Juan P. Vazquez, Corinne Pettigrew, Yuxin Zhu, Claire Anderson, Guray Erus, Christos Davatzikos, Michael Miller, Abhay Moghekar, Sungtaek Oh, Chan‐Hyun Na, Marilyn Albert, Paul Worley, Anja Soldan   +12 more
wiley   +1 more source

Plasma Proteomic Signatures for Alzheimer's Disease: Comparable Accuracy to ATN Biomarkers and Cross‐Platform Validation

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background There is growing recognition of the potential of plasma proteomics for Alzheimer's Disease (AD) risk assessment and disease characterization. However, differences between proteomics platforms introduce uncertainties regarding cross‐platform applicability.
Manyue Hu, Oliver Robinson, Christina M. Lill, Anna Matton, Raquel Puerta, Pilar Sanz, Merce Boada, Agustín Ruiz, Lefkos Middleton, for the Alzheimer's Disease Neuroimaging Initiative   +9 more
wiley   +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

Malfustection: Obfuscated Malware Detection and Malware Classification with Data Shortage by Combining Semi-Supervised and Contrastive Learning [PDF]

, 2021
Mohammad Mahdi Maghouli, Mohamadreza Fereydooni, Monireh Abdoos, Mojtaba Vahidi-Asl   +3 more
openalex   +1 more source

Predicting Epileptogenic Tubers in Patients With Tuberous Sclerosis Complex Using a Fusion Model Integrating Lesion Network Mapping and Machine Learning

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Accurate localization of epileptogenic tubers (ETs) in patients with tuberous sclerosis complex (TSC) is essential but challenging, as these tubers lack distinct pathological or genetic markers to differentiate them from other cortical tubers.
Tinghong Liu, Qi Wang, Suhui Kuang, Dezhi Cao, Ping Ding, Shaohui Zhang, Haihua Wei, Zhirong Wei, Jinshan Xu, Xinyu Huang, Bing Liu, Shuli Liang   +11 more
wiley   +1 more source