AIMC Topic: Algorithms

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Prognostic Assessment of COVID-19 in the Intensive Care Unit by Machine Learning Methods: Model Development and Validation.

Journal of medical Internet research
BACKGROUND: Patients with COVID-19 in the intensive care unit (ICU) have a high mortality rate, and methods to assess patients' prognosis early and administer precise treatment are of great significance.

Predicting High Coronary Artery Calcium Score From Retinal Fundus Images With Deep Learning Algorithms.

Translational vision science & technology
PURPOSE: To evaluate high accumulation of coronary artery calcium (CAC) from retinal fundus images with deep learning technologies as an inexpensive and radiation-free screening method.

Machine learning assisted intraoperative assessment of brain tumor margins using HRMAS NMR spectroscopy.

PLoS computational biology
Complete resection of the tumor is important for survival in glioma patients. Even if the gross total resection was achieved, left-over micro-scale tissue in the excision cavity risks recurrence. High Resolution Magic Angle Spinning Nuclear Magnetic ...

Spider webs inspiring soft robotics.

Journal of the Royal Society, Interface
In soft robotics, bio-inspiration ranges from hard- to software. Orb web spiders provide excellent examples for both. Adapted sensors on their legs may use morphological computing to fine-tune feedback loops that supervise the handling and accurate p...

Machine-learning algorithms for predicting hospital re-admissions in sickle cell disease.

British journal of haematology
Reducing preventable hospital re-admissions in Sickle Cell Disease (SCD) could potentially improve outcomes and decrease healthcare costs. In a retrospective study of electronic health records, we hypothesized Machine-Learning (ML) algorithms may out...

Deep-learning-assisted detection and segmentation of rib fractures from CT scans: Development and validation of FracNet.

EBioMedicine
BACKGROUND: Diagnosis of rib fractures plays an important role in identifying trauma severity. However, quickly and precisely identifying the rib fractures in a large number of CT images with increasing number of patients is a tough task, which is al...

Deep learning-based clustering robustly identified two classes of sepsis with both prognostic and predictive values.

EBioMedicine
BACKGROUND: Sepsis is a heterogenous syndrome and individualized management strategy is the key to successful treatment. Genome wide expression profiling has been utilized for identifying subclasses of sepsis, but the clinical utility of these subcla...

LDA filter: A Latent Dirichlet Allocation preprocess method for Weka.

PloS one
This work presents an alternative method to represent documents based on LDA (Latent Dirichlet Allocation) and how it affects to classification algorithms, in comparison to common text representation. LDA assumes that each document deals with a set o...

Generation of 2-mode scale-free graphs for link-level internet topology modeling.

PloS one
Comprehensive analysis that aims to understand the topology of real-world networks and the development of algorithms that replicate their characteristics has been significant research issues. Although the accuracy of newly developed network protocols...

Comprehensive Study on Molecular Supervised Learning with Graph Neural Networks.

Journal of chemical information and modeling
This work considers strategies to develop accurate and reliable graph neural networks (GNNs) for molecular property predictions. Prediction performance of GNNs is highly sensitive to the change in various parameters due to the inherent challenges in ...