Results 51 to 60 of about 95,703 (260)

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

Unsupervised classification of noisy chromosomes [PDF]

Bioinformatics, 2001
Abstract Motivation: Almost all methods of chromosome recognition assume supervised training; i.e. we are given correctly classified chromosomes to start the training phase. Noise, if any, is confined only in the representation of the chromosomes and not in the classification of the chromosomes.
openaire   +2 more sources

Alzheimer's Disease Biomarkers Measured by Capillary Blood Collection Versus Venous Plasma and Cerebrospinal Fluid

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Blood biomarkers are increasingly critical for non‐invasive Alzheimer's Disease (AD) diagnostics and research but typically require on‐site processing. Remote point‐of‐care collection methods could enhance biomarker testing in clinical and research settings.
Sara Ho, Ziling Shen, Alexandria Lewis, Megha Patel, Anny Zheng, Gianna Proscino, Thaovy Ho, Jiangxia Wang, Marilyn Albert, Abhay Moghekar   +9 more
wiley   +1 more source

The Spatio-Temporal Equalization Sliding-Window Distribution Distance Maximization Based on Unsupervised Learning for Online Event-Related Potential-Based Brain–Computer Interfaces

Machines
Brain–computer interfaces (BCIs) provide a direct communication pathway between the central nervous system and external environments, enabling human–machine interaction control.
Haoye Wang, Jing Jin, Xinjie He, Shurui Li, Andrzej Cichocki   +4 more
doaj   +1 more source

Unsupervised Feature Selection Based on Ultrametricity and Sparse Training Data: A Case Study for the Classification of High-Dimensional Hyperspectral Data

Remote Sensing, 2018
In this paper, we investigate the potential of unsupervised feature selection techniques for classification tasks, where only sparse training data are available.
Patrick Erik Bradley, Sina Keller, Martin Weinmann   +2 more
doaj   +1 more source

An Unsupervised Sentiment Classification Method Based on Multi-Level Fuzzy Computing and Multi-Criteria Fusion

IEEE Access, 2020
With the rapid growth of user-generated content, unsupervised methods that do not require label training data have gradually become a research focus in the field of sentiment classification and natural language processing.
Bingkun Wang, Weina He, Zhen Yang, Shufeng Xiong   +3 more
doaj   +1 more source

Anticoagulation Treatment Response Among Phenotypic ESUS Clusters: Evidence From CASPR

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To evaluate treatment effect heterogeneity across phenotypic clusters of patients with cryptogenic embolic stroke using causal inference methods. Methods From a retrospective, multicenter cohort of patients with cryptogenic embolic stroke, we estimated the treatment effect of anticoagulation versus antiplatelet therapy in patients ...
Elena Badillo Goicoechea, Patrick Ellsworth, James E. Siegler, James R. Brorson, Christina M. Lineback, Frank G. Conyers, Deborah Kerrigan, Kelsey Eklund, Shadi Yaghi, Farid Khasiyev, Emiliya Melkumova, Collin J. Culbertson, Marissa D'Souza, Dinesh V. Jillella, Patrick Glover, Hassan Aboul‐Nour, Fadi Nahab, Mahan Shahrivari, Simona Nedelcu, David S. Liebeskind, Matthew M. Smith, Aaron Rothstein, Anna Bowman, Alicia Zha, Narendra Kala, Ahmad Abu Qdais, Sami Al Kasab, Mudassir Farooqui, Diana Rojas‐Soto, Yasmin Aziz, Franziska Herpich, Jean‐Philippe Daniel, Sean L. Thompson, Vivek Patel, Thanh N. Nguyen, Siddharth Sehgal, Wenzheng Yu, Wayneho Kam, Russel Van Coevering, Oana M. Dumitrascu, Muhammad Alvi, Balaji Krishnaiah, Setareh Salehi Omran, Guillermo Linares, Eesha Singh, Hamid Ali, Mary Penckofer, Jesse M. Thon, Shani Mannion, Dalia Chahien, Lucia Chen, Fawad Talat, Mehdi Abbasi, Richa Sharma   +53 more
wiley   +1 more source

Supervised versus unsupervised approaches to classification of accelerometry data

Ecology and Evolution, 2023
Sophisticated animal‐borne sensor systems are increasingly providing novel insight into how animals behave and move. Despite their widespread use in ecology, the diversity and expanding quality and quantity of data they produce have created a need for ...
Maitreyi Sur, Jonathan C. Hall, Joseph Brandt, Molly Astell, Sharon A. Poessel, Todd E. Katzner   +5 more
doaj   +1 more source

Diffusion Basis Spectrum Imaging of Tissue Microstructure and Early Treatment in Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Conventional MRI cannot resolve the coexisting pathological processes within multiple sclerosis tissue. Diffusion Basis Spectrum Imaging decomposes the diffusion signal into fiber, cell, and hindered ratios indexing axonal integrity, cellularity, and extracellular space, respectively.
Apisit Kaewsanit, Aime Luna, Bradley Judge, Nicole Shelley, Karl Friedrichsen, Jayashree Rajamanickam, Zhude Tu, Yong Wang, Tammie L. S. Benzinger, Qing Wang, Matthew R. Brier   +10 more
wiley   +1 more source

Artificial Intelligence in Systemic Sclerosis: Clinical Applications, Challenges, and Future Directions

Arthritis Care &Research, EarlyView.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos, José Miguel Sequí‐Sabater, Diego Benavent   +2 more
wiley   +1 more source