AIMC Topic: Algorithms

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Certainty-Guided Cross Contrastive Learning for Semi-Supervised Medical Image Segmentation.

IEEE transactions on bio-medical engineering
Semi-supervised learning (SSL) enables the accurate segmentation of medical images with limited available labeled data. However, its performance usually lags fully supervised methods that require the whole dataset to be labeled. We propose a novel SS...

Optimizing surgical efficiency: predicting case duration of common general surgery procedures using machine learning.

Surgical endoscopy
BACKGROUND: Accurate prediction of surgical duration is critical to optimizing use of operating room resources. Currently, cases are scheduled using subjective estimates of length by surgeons, relying heavily on prior experience. This study aims to d...

Emerging Technologies and Algorithms for Periodontal Screening and Risk of Disease Progression in Non-Dental Settings: A Scoping Review.

Journal of clinical periodontology
AIM: To evaluate different tools to screen for periodontal diseases and/or evaluate the risk for disease progression in non-dental clinical settings.

Development and validation of a SOTA-based system for biliopancreatic segmentation and station recognition system in EUS.

Surgical endoscopy
BACKGROUND: Endoscopic ultrasound (EUS) is a vital tool for diagnosing biliopancreatic disease, offering detailed imaging to identify key abnormalities. Its interpretation demands expertise, which limits its accessibility for less trained practitione...

Self-Supervised Optimization of RF Data Coherence for Improving Breast Reflection UCT Reconstruction.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
The reflection ultrasound computed tomography (UCT) is gaining prominence as an essential instrument for breast cancer screening. However, reflection UCT quality is often compromised by the variability in sound speed across breast tissue. Traditional...

Insights on Scan-Specific Deep-Learning Strategies for Brain MRI Parallel Imaging Reconstruction.

NMR in biomedicine
Scan-specific deep learning strategies have been proposed for parallel imaging reconstruction in which auto-calibrated signals (ACS) are used for training. Here, we introduce methods to objectively optimize architecture and training details. In addit...

Artificial neural networks computing for heat transfer flow of hybrid nanofluid in rectangular geometry.

Computers in biology and medicine
This study explores the complex dynamics of heat transfer in hybrid nanofluid flow, focusing on the unsteady squeezing motion of Graphene-FeO/water confined between two parallel plates under the influence of a magnetic field. The lower plate is assum...

Stabilization of the human heartbeat using adaptive controller-based optimized deep policy gradient.

Computers in biology and medicine
Stabilizing the cardiac rhythm is imperative for preserving cardiovascular health and preventing life-threatening arrhythmias. The stabilization of the heartbeat through traditional control methods presents significant challenges due to the intricate...

Performance analysis of machine learning algorithms for the prediction of disinfection byproducts formation during chlorination: Effect of background water characteristics.

Journal of environmental management
This study investigated the comparison of the nonlinear machine learning algorithms and linear regression models to predict the formation of trihalomethanes (THM4), haloacetic acids (HAA5 and HAA9), and haloacetonitriles (HAN4 and HAN6) under uniform...

Analysis of disease severity and mortality prediction using machine learning during COVID-19.

Acta psychologica
This paper focuses on how machine learning (ML) algorithms and applications have been used to analyze disease severity and mortality prediction in COVID-19 research. In the past, simpler statistical and epidemiological methods were more commonly used...