Topological feature extraction and visualization of whole slide images using graph neural networks
Whole-slide images (WSI) are digitized representations of thin sections of stained tissue
from various patient sources (biopsy, resection, exfoliation, fluid) and often exceed 100,000 …
from various patient sources (biopsy, resection, exfoliation, fluid) and often exceed 100,000 …
[HTML][HTML] A blood atlas of COVID-19 defines hallmarks of disease severity and specificity
DJ Ahern, Z Ai, M Ainsworth, C Allan, A Allcock… - Cell, 2022 - cell.com
Treatment of severe COVID-19 is currently limited by clinical heterogeneity and incomplete
description of specific immune biomarkers. We present here a comprehensive multi-omic …
description of specific immune biomarkers. We present here a comprehensive multi-omic …
giotto-tda:: A topological data analysis toolkit for machine learning and data exploration
We introduce giotto-tda, a Python library that integrates high-performance topological data
analysis with machine learning via a scikit-learn-compatible API and state-of-the-art C++ …
analysis with machine learning via a scikit-learn-compatible API and state-of-the-art C++ …
Topological methods in machine learning: A tutorial for practitioners
B Coskunuzer, CG Akçora - arXiv preprint arXiv:2409.02901, 2024 - arxiv.org
Topological Machine Learning (TML) is an emerging field that leverages techniques from
algebraic topology to analyze complex data structures in ways that traditional machine …
algebraic topology to analyze complex data structures in ways that traditional machine …
Visualization of exhaled breath metabolites reveals distinct diagnostic signatures for acute cardiorespiratory breathlessness
W Ibrahim, MJ Wilde, RL Cordell… - Science translational …, 2022 - science.org
Acute cardiorespiratory breathlessness accounts for one in eight of all emergency
hospitalizations. Early, noninvasive diagnostic testing is a clinical priority that allows rapid …
hospitalizations. Early, noninvasive diagnostic testing is a clinical priority that allows rapid …
Interpreting deep learning features for myoelectric control: A comparison with handcrafted features
Existing research on myoelectric control systems primarily focuses on extracting
discriminative characteristics of the electromyographic (EMG) signal by designing …
discriminative characteristics of the electromyographic (EMG) signal by designing …
Machine learning enabled tailor-made design of application-specific metal–organic frameworks
X Zhang, K Zhang, Y Lee - ACS applied materials & interfaces, 2019 - ACS Publications
In the development of advanced nanoporous materials, one clear and unavoidable
challenge in hand is the sheer size (in principle, infinite) of the materials space to be …
challenge in hand is the sheer size (in principle, infinite) of the materials space to be …
On variational learning of controllable representations for text without supervision
The variational autoencoder (VAE) can learn the manifold of natural images on certain
datasets, as evidenced by meaningful interpolating or extrapolating in the continuous latent …
datasets, as evidenced by meaningful interpolating or extrapolating in the continuous latent …
Stratification of diabetes in the context of comorbidities, using representation learning and topological data analysis
Diabetes is a heterogenous, multimorbid disorder with a large variation in manifestations,
trajectories, and outcomes. The aim of this study is to validate a novel machine learning …
trajectories, and outcomes. The aim of this study is to validate a novel machine learning …
SFCM: A fuzzy clustering algorithm of extracting the shape information of data
Topological data analysis is a new theoretical trend using topological techniques to mine
data. This approach helps determine topological data structures. It focuses on investigating …
data. This approach helps determine topological data structures. It focuses on investigating …