AIMC Topic: Algorithms

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Clinical approaches for integrating machine learning for patients with lymphoma: Current strategies and future perspectives.

British journal of haematology
Machine learning (ML) approaches have been applied in the diagnosis and prediction of haematological malignancies. The consideration of ML algorithms to complement or replace current standard of care approaches requires investigation into the methods...

Robust and efficient abdominal CT segmentation using shape constrained multi-scale attention network.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: Although many deep learning-based abdominal multi-organ segmentation networks have been proposed, the various intensity distributions and organ shapes of the CT images from multi-center, multi-phase with various diseases introduce new challe...

Predicting the survival of patients with pancreatic neuroendocrine neoplasms using deep learning: A study based on Surveillance, Epidemiology, and End Results database.

Cancer medicine
BACKGROUND: The study aims to evaluate the performance of three advanced machine learning algorithms and a traditional Cox proportional hazard (CoxPH) model in predicting the overall survival (OS) of patients with pancreatic neuroendocrine neoplasms ...

Eliminating the need for manual segmentation to determine size and volume from MRI. A proof of concept on segmenting the lateral ventricles.

PloS one
Manual segmentation, which is tedious, time-consuming, and operator-dependent, is currently used as the gold standard to validate automatic and semiautomatic methods that quantify geometries from 2D and 3D MR images. This study examines the accuracy ...

Henry gas solubility optimization double machine learning classifier for neurosurgical patients.

PloS one
This study aims to predict head trauma outcome for Neurosurgical patients in children, adults, and elderly people. As Machine Learning (ML) algorithms are helpful in healthcare field, a comparative study of various ML techniques is developed. Several...

Machine learning-based approach for efficient prediction of toxicity of chemical gases using feature selection.

Journal of hazardous materials
Toxic gases can be fatal as they damage many living tissues, especially the nervous and respiratory systems. They can cause permanent damage for many years by harming environmental tissue and living organisms. They can also cause mass deaths when use...

Distance metric learning based on the class center and nearest neighbor relationship.

Neural networks : the official journal of the International Neural Network Society
Distance metric learning has been a promising technology to improve the performance of algorithms related to distance metrics. The existing distance metric learning methods are either based on the class center or the nearest neighbor relationship. In...

Platform for investigating continuum manipulator behavior in orthopedics.

International journal of computer assisted radiology and surgery
PURPOSE: The use of robotic continuum manipulators has been proposed to facilitate less-invasive orthopedic surgical procedures. While tools and strategies have been developed, critical challenges such as system control and intra-operative guidance a...

Rapid and Accurate Identification of Cell Phenotypes of Different Drug Mechanisms by Using Single-Cell Fluorescence Images Via Deep Learning.

Analytical chemistry
Identification of a drug mechanism is vital for drug development. However, it often resorts to the expensive and cumbersome omics methods along with complex data analysis. Herein, we developed a methodology to analyze organelle staining images of sin...

Brain-inspired multimodal hybrid neural network for robot place recognition.

Science robotics
Place recognition is an essential spatial intelligence capability for robots to understand and navigate the world. However, recognizing places in natural environments remains a challenging task for robots because of resource limitations and changing ...