4.6 Article

The shape of cancer relapse: Topological data analysis predicts recurrence in paediatric acute lymphoblastic leukaemia

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Review Computer Science, Artificial Intelligence

Interpretability in the medical field: A systematic mapping and review study

Hajar Hakkoum et al.

Summary: The field of machine learning has been rapidly growing, especially in the medical field. However, the interpretability of ML models remains a challenge, hindering its adoption by physicians. This study conducted a systematic review of interpretability techniques applied in the medical field. The results showed an increase in studies on interpretability, with a focus on solution proposals and experiment-based evaluations. Diagnosis, oncology, and classification were the most frequently studied medical tasks and ML objectives. Artificial neural networks were the most commonly used ML black-box techniques. Global interpretability techniques, such as rules, were dominant in explanations. The study suggests the need for further research in disciplines beyond diagnosis and classification, the exploration of local interpretability techniques, and quantitative evaluation and physician involvement to gain trust in black-box models in medical environments.

APPLIED SOFT COMPUTING (2022)

Review Computer Science, Interdisciplinary Applications

Topological data analysis in biomedicine: A review

Yara Skaf et al.

Summary: In recent years, the utilization of digital technologies in biomedicine has increased dramatically, leading to a surge in available data. However, current data analysis tools are struggling to extract meaningful knowledge from this wealth of information. This article introduces the concept of topological data analysis (TDA), a mathematical method grounded in algebraic topology, that aims to describe and utilize features related to the shape of data. The article provides a conceptual discussion of TDA and surveys its applications in scientific research, with the goal of making these techniques more accessible to non-mathematicians.

JOURNAL OF BIOMEDICAL INFORMATICS (2022)

Article Biochemical Research Methods

Determining clinically relevant features in cytometry data using persistent homology

Soham Mukherjee et al.

Summary: The study applies persistent homology to analyze cytometry data of healthy donors and COVID-19 patients, revealing structural differences between the two groups despite random variations in the data. This method is effective in capturing topological features in datasets, potentially leading to the discovery of novel insights.

PLOS COMPUTATIONAL BIOLOGY (2022)

Article Biochemical Research Methods

A topological data analytic approach for discovering biophysical signatures in protein dynamics

Wai Shing Tang et al.

Summary: In this paper, the authors propose SINATRA Pro, a computational framework for extracting key structural features between two sets of proteins. SINATRA Pro outperforms standard techniques in pinpointing the physical locations of both static and dynamic signatures across various types of protein ensembles, and it does so with improved resolution.

PLOS COMPUTATIONAL BIOLOGY (2022)

Article Multidisciplinary Sciences

Multiscale topology characterizes dynamic tumor vascular networks

Bernadette J. Stolz et al.

Summary: This article showcases how topological data analysis can be used to characterize the geometric, spatial, and temporal organization of vascular networks. The proposed method captures multiscale features and vessel connectivity, enabling quantification of abnormal structural features and variation in vascular networks. The authors validate the method through analysis of images collected using different imaging modalities, and quantify the effects of antibody modulation and radiotherapy on vascular architecture.

SCIENCE ADVANCES (2022)

Article Oncology

Identification of Leukemia-Associated Immunophenotypes by Databaseguided Flow Cytometry Provides a Highly Sensitive and Reproducible Strategy for the Study of Measurable Residual Disease in Acute Myeloblastic Leukemia

Paula Pinero et al.

Summary: The immunophenotypic characterization of acute myeloid leukemia is crucial for accurate diagnosis and follow-up. This study presents an automated multidimensional strategy to identify and characterize leukemia-associated immunophenotypes (LAIPs) and detect emerging aberrations in AML patients during follow-up. The proposed DFN/LAIP strategy improves the sensitivity and specificity of minimal residual disease monitoring and provides an objective method for LAIP identification and characterization.

CANCERS (2022)

Article Oncology

High-Dimensional Analysis of Single-Cell Flow Cytometry Data Predicts Relapse in Childhood Acute Lymphoblastic Leukaemia

Salvador Chulian et al.

Summary: This study analyzed flow cytometry data from 56 pediatric B-cell Acute Lymphoblastic Leukemia patients to assess the prognostic potential of immunophenotypical marker expression intensity. By constructing classifiers based on CD38 expression, it was found that subexpression of CD38 marker is associated with the probability of relapse.

CANCERS (2021)

Article Multidisciplinary Sciences

Multiparameter persistent homology landscapes identify immune cell spatial patterns in tumors

Oliver Vipond et al.

Summary: This article introduces a mathematical method, multiparameter persistent homology (MPH), for analyzing spatial data of complex systems. The application of MPH landscapes in studying immune cell infiltration and the tumor microenvironment demonstrates its advantages over existing spatial statistics, allowing for better quantification and comparison of features in different cell locations.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2021)

Editorial Material Medicine, General & Internal

Personalising cancer medicine with prognostic markers

David J. Kerr et al.

EBIOMEDICINE (2021)

Article Biochemical Research Methods

Topological data analysis distinguishes parameter regimes in the Anderson-Chaplain model of angiogenesis

John T. Nardini et al.

Summary: By simulating the Anderson-Chaplain model of angiogenesis at different parameter values and using topological data analysis, researchers were able to stratify the parameter space into regions with similar vessel morphology. This method can be widely applied to other synthetic and experimental data fields, including wound healing, development, and plant biology.

PLOS COMPUTATIONAL BIOLOGY (2021)

Review Computer Science, Artificial Intelligence

Applications of Topological Data Analysis in Oncology

Anuraag Bukkuri et al.

Summary: The information age has led to an explosion of biomedical data, requiring new algorithms for analysis and translation into clinical applications; Topological data analysis (TDA) utilizes tools from algebraic topology to provide a framework for analyzing high-dimensional, incomplete, and noisy biomedical data; In the field of oncology, TDA has shown success in predicting treatment responses, tumor segmentation, disease classification, and other applications.

FRONTIERS IN ARTIFICIAL INTELLIGENCE (2021)

Article Statistics & Probability

Predicting Clinical Outcomes in Glioblastoma: An Application of Topological and Functional Data Analysis

Lorin Crawford et al.

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2020)

Article Multidisciplinary Sciences

Topological data analysis of zebrafish patterns

Melissa R. McGuirl et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2020)

Article Multidisciplinary Sciences

Rates and trends of childhood acute lymphoblastic leukaemia: an epidemiology study

Ameer Kakaje et al.

SCIENTIFIC REPORTS (2020)

Article Multidisciplinary Sciences

Geometric anomaly detection in data

Bernadette J. Stolz et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2020)

Article Multidisciplinary Sciences

Identification of relevant genetic alterations in cancer using topological data analysis

Raul Rabadan et al.

NATURE COMMUNICATIONS (2020)

Article Mathematics, Interdisciplinary Applications

Topological Data Analysis of Vascular Disease: A Theoretical Framework

John Nicponski et al.

FRONTIERS IN APPLIED MATHEMATICS AND STATISTICS (2020)

Article Computer Science, Artificial Intelligence

Automatic acute lymphoblastic leukemia classification model using social spider optimization algorithm

Ahmed T. Sahlo et al.

SOFT COMPUTING (2019)

Article Multidisciplinary Sciences

Next-generation characterization of the Cancer Cell Line Encyclopedia

Mahmoud Ghandi et al.

NATURE (2019)

Article Computer Science, Interdisciplinary Applications

A Topological Representation of Branching Neuronal Morphologies

Lida Kanari et al.

NEUROINFORMATICS (2018)

Article Chemistry, Physical

Persistent homology analysis of ion aggregations and hydrogen-bonding networks

Kelin Xia

PHYSICAL CHEMISTRY CHEMICAL PHYSICS (2018)

Article Mathematics

WHAT CAN TOPOLOGY TELL US ABOUT THE NEURAL CODE?

Carina Curto

BULLETIN OF THE AMERICAN MATHEMATICAL SOCIETY (2017)

Article Multidisciplinary Sciences

Sensitive detection of rare disease-associated cell subsets via representation learning

Eirini Arvaniti et al.

NATURE COMMUNICATIONS (2017)

Review Oncology

Acute lymphoblastic leukemia: a comprehensive review and 2017 update

T. Terwilliger et al.

BLOOD CANCER JOURNAL (2017)

Article Biochemical Research Methods

FloReMi: Flow density survival regression using minimal feature redundancy

Sofie Van Gassen et al.

CYTOMETRY PART A (2016)

Review Pharmacology & Pharmacy

L-asparaginase in the treatment of patients with acute lymphoblastic leukemia

Rachel A. Egler et al.

JOURNAL OF PHARMACOLOGY & PHARMACOTHERAPEUTICS (2016)

Article Biochemical Research Methods

FlowSOM: Using self-organizing maps for visualization and interpretation of cytometry data

Sofie Van Gassen et al.

CYTOMETRY PART A (2015)

Article Multidisciplinary Sciences

Clique topology reveals intrinsic geometric structure in neural correlations

Chad Giusti et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2015)

Article Multidisciplinary Sciences

Topological data analysis for discovery in preclinical spinal cord injury and traumatic brain injury

Jessica L. Nielson et al.

NATURE COMMUNICATIONS (2015)

Article Multidisciplinary Sciences

Topological data analysis of contagion maps for examining spreading processes on networks

Dane Taylor et al.

NATURE COMMUNICATIONS (2015)

Article Multidisciplinary Sciences

Automated identification of stratifying signatures in cellular subpopulations

Robert V. Bruggner et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2014)

Article Multidisciplinary Sciences

Topology based data analysis identifies a subgroup of breast cancers with a unique mutational profile and excellent survival

Monica Nicolau et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2011)

Editorial Material Mathematics

TOPOLOGY AND DATA

Gunnar Carlsson

BULLETIN OF THE AMERICAN MATHEMATICAL SOCIETY (2009)

Review Hematology

Flow cytometric immunophenotyping for hematologic neoplasms

Fiona E. Craig et al.

Article Engineering, Biomedical

A multidimensional classification approach for the automated analysis of flow cytometry data

Carlos Eduardo Pedreira et al.

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING (2008)

Article Computer Science, Theory & Methods

Stability of persistence diagrams

David Cohen-Steiner et al.

DISCRETE & COMPUTATIONAL GEOMETRY (2007)

Article Biotechnology & Applied Microbiology

What is a support vector machine?

William S. Noble

NATURE BIOTECHNOLOGY (2006)

Article Computer Science, Theory & Methods

Topological persistence and simplification

H Edelsbrunner et al.

DISCRETE & COMPUTATIONAL GEOMETRY (2002)

Article Computer Science, Artificial Intelligence

Random forests

L Breiman

MACHINE LEARNING (2001)