Results 81 to 90 of about 323,408 (293)

Bi‐ and Mono‐Allelic RFC1 Expansion in a North American Cohort With Idiopathic Axonal Neuropathy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective RFC1 biallelic repeat expansion is increasingly recognized as a cause of chronic idiopathic axonal polyneuropathy (CIAP), but it remains challenging to know who to test. This study aims to determine the prevalence of biallelic and monoallelic RFC1 expansions and their corresponding neuropathy phenotypes in CIAP patients and identify ...
Amro M. Stino, Lavanya Muthukumar, Evan L. Reynolds, Peter Todd, Sinem Ovunc, Sheng Chih Jin, Zitian Tang, Simone Thomas, PNRR Study Group, Ahmet Höke, Brian C. Callaghan, Sarah Berth, Vinay Chaudhry, David Cornblath, Leana Doherty, Lindsey Hayes, Hristelina Ilieva, Thomas Lloyd, Mohammad Khoshnoodi, Brett McCray, Brett Morrison, Bipasha Mukherjee‐Clavin, Lyle Ostrow, Michael Polydefkis, Ricardo Roda, Charlotte Sumner   +25 more
wiley   +1 more source

Unsupervised Cognition

Unsupervised learning methods have a soft inspiration in cognition models. To this day, the most successful unsupervised learning methods revolve around clustering samples in a mathematical space. In this paper we propose a primitive-based, unsupervised learning approach for decision-making inspired by a novel cognition framework.
Alfredo Ibias, Hector Antona, Guillem Ramirez-Miranda, Enric Guinovart, Eduard Alarcon   +4 more
openaire   +2 more sources

Unsupervised Image Captioning [PDF]

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Deep neural networks have achieved great successes on the image captioning task. However, most of the existing models depend heavily on paired image-sentence datasets, which are very expensive to acquire. In this paper, we make the first attempt to train an image captioning model in an unsupervised manner.
Yang Feng 0001, Lin Ma 0002, Wei Liu 0005, Jiebo Luo 0001   +3 more
openaire   +4 more sources

Integrated PANoptosis Profiling Identifies Immunosuppressive Subtypes and a Prognostic Signature With Functional Validation of MLKL in Glioblastoma

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective The prognosis of glioblastoma (GBM) remains highly unfavorable, largely due to high tumor heterogeneity and an immunosuppressive microenvironment. However, the functional role of PANoptosis in this context is poorly understood. Methods Patients were stratified via K‐means clustering. A risk score model was constructed using prognosis‐
Langfei Tian, Minghui Zhao, Yuanbo Hu, Kaiyue Wang, Haiguang Liu, Zetong Bai, Kebin Zheng   +6 more
wiley   +1 more source

Unsupervised Methodology for Large-Scale Tree Seedling Mapping in Diverse Forestry Settings Using UAV-Based RGB Imagery

Remote Sensing, 2023
Mapping and monitoring tree seedlings is essential for reforestation and restoration efforts. However, achieving this on a large scale, especially during the initial stages of growth, when seedlings are small and lack distinct morphological features, can
Sadeepa Jayathunga, Grant D. Pearse, Michael S. Watt   +2 more
doaj   +1 more source

Data‐Driven SuStaIn Model of Disability Progression in Amyotrophic Lateral Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To determine whether ordinal Subtype and Stage Inference (SuStaIn) applied to routine ALSFRS‐R item scores can identify reproducible disability progression patterns in amyotrophic lateral sclerosis (ALS) and provide clinically meaningful staging.
Giammarco Milella, Veria Vacchiano, Vittorio Velucci, Stefano Zoccolella, Rocco Liguori, Giovanni Defazio   +5 more
wiley   +1 more source

Anomaly detection via Gumbel Noise Score Matching

Frontiers in Artificial Intelligence
We propose Gumbel Noise Score Matching (GNSM), a novel unsupervised method to detect anomalies in categorical data. GNSM accomplishes this by estimating the scores, i.e., the gradients of log likelihoods w.r.t. inputs, of continuously relaxed categorical
Ahsan Mahmood, Junier Oliva, Martin Andreas Styner   +2 more
doaj   +1 more source

Investigating the Effectiveness of Supervised and Unsupervised Classification for Landsat Images Utilizing Classification Accuracy Assessment. [PDF]

Kirkuk Journal of Science
This study filled in gaps in 2012 Landsat-7 satellite images using the "Nearest Similar Pixel Processor" algorithm.  Changes in LU/LC coverage in Babil province were classified and tracked during the period from 1999 to 2023. Landsat-7 and Landsat-8
Hayder Jassoom, Rabab Abdoon
doaj   +1 more source

Unsupervised Adversarial Invariance

CoRR, 2018
To appear in Proceedings of NIPS ...
Ayush Jaiswal, Yue Wu 0001, Wael AbdAlmageed, Premkumar Natarajan   +3 more
openaire   +4 more sources

Unsupervised Trajectory Sampling [PDF]

, 2010
A novel methodology for efficiently sampling Trajectory Databases (TD) for mobility data mining purposes is presented. In particular, a three-step unsupervised trajectory sampling methodology is proposed, that initially adopts a symbolic vector representation of a trajectory which, using a similarity-based voting technique, is transformed to a ...
Nikos Pelekis, Ioannis Kopanakis, Costas Panagiotakis, Yannis Theodoridis   +3 more
openaire   +1 more source