AIMC Topic: Algorithms

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Development of a machine learning algorithm predicting discharge placement after surgery for spondylolisthesis.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
PURPOSE: We aimed to develop a machine learning algorithm that can accurately predict discharge placement in patients undergoing elective surgery for degenerative spondylolisthesis.

Flexible unsupervised feature extraction for image classification.

Neural networks : the official journal of the International Neural Network Society
Dimensionality reduction is one of the fundamental and important topics in the fields of pattern recognition and machine learning. However, most existing dimensionality reduction methods aim to seek a projection matrix W such that the projection Wx i...

A deep learning-based decision support system for diagnosis of OSAS using PTT signals.

Medical hypotheses
Sleep disorders, which negatively affect an individual's daily quality of life, are a common problem for most of society. The most dangerous sleep disorder is obstructive sleep apnea syndrome (OSAS), which manifests itself during sleep and can cause ...

Kidney cortex segmentation in 2D CT with U-Nets ensemble aggregation.

Diagnostic and interventional imaging
PURPOSE: This work presents our contribution to one of the data challenges organized by the French Radiology Society during the Journées Francophones de Radiologie. This challenge consisted in segmenting the kidney cortex from coronal computed tomogr...

Diagnosis of focal liver lesions from ultrasound using deep learning.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to create an algorithm that simultaneously detects and characterizes (benign vs. malignant) focal liver lesion (FLL) using deep learning.

Classification and Recognition of Ovarian Cells Based on Two-Dimensional Light Scattering Technology.

Journal of medical systems
Ovarian cancer is a very insidious malignant tumor. In order to detect ovarian cancer cells early, the classification and recognition of ovarian cancer cells is mainly studied by two-dimensional light scattering technology. Firstly, a single-cell two...

GO functional similarity clustering depends on similarity measure, clustering method, and annotation completeness.

BMC bioinformatics
BACKGROUND: Biological knowledge, and therefore Gene Ontology annotation sets, for human genes is incomplete. Recent studies have reported that biases in available GO annotations result in biased estimates of functional similarities of genes, but it ...

Evaluating reproducibility of AI algorithms in digital pathology with DAPPER.

PLoS computational biology
Artificial Intelligence is exponentially increasing its impact on healthcare. As deep learning is mastering computer vision tasks, its application to digital pathology is natural, with the promise of aiding in routine reporting and standardizing resu...

An Efficient Deep Learning Approach to Pneumonia Classification in Healthcare.

Journal of healthcare engineering
This study proposes a convolutional neural network model trained from scratch to classify and detect the presence of pneumonia from a collection of chest X-ray image samples. Unlike other methods that rely solely on transfer learning approaches or tr...

A multi hidden recurrent neural network with a modified grey wolf optimizer.

PloS one
Identifying university students' weaknesses results in better learning and can function as an early warning system to enable students to improve. However, the satisfaction level of existing systems is not promising. New and dynamic hybrid systems are...