AI Medical Compendium Topic

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Cluster Analysis

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Explainable hierarchical clustering for patient subtyping and risk prediction.

Experimental biology and medicine (Maywood, N.J.)
We present a pipeline in which machine learning techniques are used to automatically identify and evaluate subtypes of hospital patients admitted between 2017 and 2021 in a large UK teaching hospital. Patient clusters are determined using routinely c...

SPIN-CGNN: Improved fixed backbone protein design with contact map-based graph construction and contact graph neural network.

PLoS computational biology
Recent advances in deep learning have significantly improved the ability to infer protein sequences directly from protein structures for the fix-backbone design. The methods have evolved from the early use of multi-layer perceptrons to convolutional ...

Establishment of Biliary Atresia Prognostic Classification System via Survival-Based Forward Clustering - A New Biliary Atresia Classification.

Indian journal of pediatrics
OBJECTIVES: To develop a machine learning algorithm with prognosis data to identify different clinical phenotypes of biliary atresia (BA) and provide instructions for choosing treatment schemes.

Black-box attacks on dynamic graphs via adversarial topology perturbations.

Neural networks : the official journal of the International Neural Network Society
Research and analysis of attacks on dynamic graph is beneficial for information systems to investigate vulnerabilities and strength abilities in resisting malicious attacks. Existing attacks on dynamic graphs mainly focus on rewiring original graph s...

Combining data discretization and missing value imputation for incomplete medical datasets.

PloS one
Data discretization aims to transform a set of continuous features into discrete features, thus simplifying the representation of information and making it easier to understand, use, and explain. In practice, users can take advantage of the discretiz...

Exploration of street space architectural color measurement based on street view big data and deep learning-A case study of Jiefang North Road Street in Tianjin.

PloS one
Urban space architectural color is the first feature to be perceived in a complex vision beyond shape, texture and material, and plays an important role in the expression of urban territory, humanity and style. However, because of the difficulty of c...

A hybrid stacked ensemble and Kernel SHAP-based model for intelligent cardiotocography classification and interpretability.

BMC medical informatics and decision making
BACKGROUND: Intelligent cardiotocography (CTG) classification can assist obstetricians in evaluating fetal health. However, high classification performance is often achieved by complex machine learning (ML)-based models, which causes interpretability...

Interpretable unsupervised learning enables accurate clustering with high-throughput imaging flow cytometry.

Scientific reports
A primary challenge of high-throughput imaging flow cytometry (IFC) is to analyze the vast amount of imaging data, especially in applications where ground truth labels are unavailable or hard to obtain. We present an unsupervised deep embedding algor...

Clustering Methods for Vibro-Acoustic Sensing Features as a Potential Approach to Tissue Characterisation in Robot-Assisted Interventions.

Sensors (Basel, Switzerland)
This article provides a comprehensive analysis of the feature extraction methods applied to vibro-acoustic signals (VA signals) in the context of robot-assisted interventions. The primary objective is to extract valuable information from these signal...

Shaping the future of chronic disease management: Insights into patient needs for AI-based homecare systems.

International journal of medical informatics
BACKGROUND: The rising demand for healthcare resources, especially in chronic disease management, has elevated the importance of Artificial Intelligence (AI) in healthcare. While AI-based homecare systems are being developed, the perspectives of chro...