AIMC Topic: Machine Learning

Clear Filters Showing 10351 to 10360 of 34417 articles

Learning-Assisted Fast Determination of Regularization Parameter in Constrained Image Reconstruction.

IEEE transactions on bio-medical engineering
OBJECTIVE: To leverage machine learning (ML) for fast selection of optimal regularization parameter in constrained image reconstruction.

Using Artificial Intelligence to predict outcomes of operatively managed neck of femur fractures.

British journal of hospital medicine (London, England : 2005)
Patients with neck of femur fractures present a tremendous public health problem that leads to a high incidence of death and dysfunction. An essential factor is the postoperative length of stay, which heavily impacts hospital costs and the quality o...

Testing Machine Learning Models to Predict Postoperative Ileus after Colorectal Surgery.

Current oncology (Toronto, Ont.)
Postoperative ileus (POI) is a common complication after colorectal surgery, leading to increased hospital stay and costs. This study aimed to explore patient comorbidities that contribute to the development of POI in the colorectal surgical populat...

Leveraging permutation testing to assess confidence in positive-unlabeled learning applied to high-dimensional biological datasets.

BMC bioinformatics
BACKGROUND: Compared to traditional supervised machine learning approaches employing fully labeled samples, positive-unlabeled (PU) learning techniques aim to classify "unlabeled" samples based on a smaller proportion of known positive examples. This...

Machine learning of dissection photographs and surface scanning for quantitative 3D neuropathology.

eLife
We present open-source tools for three-dimensional (3D) analysis of photographs of dissected slices of human brains, which are routinely acquired in brain banks but seldom used for quantitative analysis. Our tools can: (1) 3D reconstruct a volume fro...

Machine learning constructs a diagnostic prediction model for calculous pyonephrosis.

Urolithiasis
In order to provide decision-making support for the auxiliary diagnosis and individualized treatment of calculous pyonephrosis, the study aims to analyze the clinical features of the condition, investigate its risk factors, and develop a prediction m...

ARKA: a framework of dimensionality reduction for machine-learning classification modeling, risk assessment, and data gap-filling of sparse environmental toxicity data.

Environmental science. Processes & impacts
Due to the lack of experimental toxicity data for environmental chemicals, there arises a need to fill data gaps by approaches. One of the most commonly used approaches for toxicity assessment of small datasets is the Quantitative Structure-Activit...

TacPrint: Visualizing the Biomechanical Fingerprint in Table Tennis.

IEEE transactions on visualization and computer graphics
Table tennis is a sport that demands high levels of technical proficiency and body coordination from players. Biomechanical fingerprints can provide valuable insights into players' habitual movement patterns and characteristics, allowing them to iden...

A Neurosurgical Readmissions Reduction Program in an Academic Hospital Leveraging Machine Learning, Workflow Analysis, and Simulation.

Applied clinical informatics
BACKGROUND:  Predicting 30-day hospital readmissions is crucial for improving patient outcomes, optimizing resource allocation, and achieving financial savings. Existing studies reporting the development of machine learning (ML) models predictive of ...

Machine learning algorithms to predict healthcare-seeking behaviors of mothers for acute respiratory infections and their determinants among children under five in sub-Saharan Africa.

Frontiers in public health
BACKGROUND: Acute respiratory infections (ARIs) are the leading cause of death in children under the age of 5 globally. Maternal healthcare-seeking behavior may help minimize mortality associated with ARIs since they make decisions about the kind and...