AIMC Topic: Unsupervised Machine Learning
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Identifying definite patterns of unmet needs in patients with multiple sclerosis using unsupervised machine learning.
Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
Feb 23, 2024
INTRODUCTION: People with multiple sclerosis (PwMS) exhibit a spectrum of needs that extend beyond solely disease-related determinants. Investigating unmet needs from the patient perspective may address daily difficulties and optimize care. Our aim w...
UDRSNet: An unsupervised deformable registration module based on image structure similarity.
Medical physics
Feb 14, 2024
BACKGROUND: Image registration is a challenging problem in many clinical tasks, but deep learning has made significant progress in this area over the past few years. Real-time and robust registration has been made possible by supervised transformatio...
How Socio-economic Inequalities Cluster People with Diabetes in Malaysia: Geographic Evaluation of Area Disparities Using a Non-parameterized Unsupervised Learning Method.
Journal of epidemiology and global health
Feb 5, 2024
Accurate assessments of epidemiological associations between health outcomes and routinely observed proximal and distal determinants of health are fundamental for the execution of effective public health interventions and policies. Methods to couple ...
[Feeling analysis on allergen immunotherapy on using an unsupervised machine learning model].
Revista alergia Mexico (Tecamachalco, Puebla, Mexico : 1993)
Feb 1, 2024
OBJECTIVE: Analyze feelings about allergen-specific immunotherapy on using the VADER model VADER () model.
A multi-module algorithm for heartbeat classification based on unsupervised learning and adaptive feature transfer.
Computers in biology and medicine
Jan 28, 2024
The scarcity of annotated data is a common issue in the realm of heartbeat classification based on deep learning. Transfer learning (TL) has emerged as an effective strategy for addressing this issue. However, current TL techniques in this realm over...
Segmenting mechanically heterogeneous domains via unsupervised learning.
Biomechanics and modeling in mechanobiology
Jan 13, 2024
From biological organs to soft robotics, highly deformable materials are essential components of natural and engineered systems. These highly deformable materials can have heterogeneous material properties, and can experience heterogeneous deformatio...
Reclassification of ASFV into 7 Biotypes Using Unsupervised Machine Learning.
Viruses
Dec 30, 2023
In 2007, an outbreak of African swine fever (ASF), a deadly disease of domestic swine and wild boar caused by the African swine fever virus (ASFV), occurred in Georgia and has since spread globally. Historically, ASFV was classified into 25 different...
Unsupervised learning of mid-level visual representations.
Current opinion in neurobiology
Dec 27, 2023
Recently, a confluence between trends in neuroscience and machine learning has brought a renewed focus on unsupervised learning, where sensory processing systems learn to exploit the statistical structure of their inputs in the absence of explicit tr...
Unsupervised learning of stationary and switching dynamical system models from Poisson observations.
Journal of neural engineering
Dec 12, 2023
. Investigating neural population dynamics underlying behavior requires learning accurate models of the recorded spiking activity, which can be modeled with a Poisson observation distribution. Switching dynamical system models can offer both explanat...
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