AI Medical Compendium Topic:
Models, Biological

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The Use of Deep Learning to Predict Stroke Patient Mortality.

International journal of environmental research and public health
The increase in stroke incidence with the aging of the Korean population will rapidly impose an economic burden on society. Timely treatment can improve stroke prognosis. Awareness of stroke warning signs and appropriate actions in the event of a str...

MHCSeqNet: a deep neural network model for universal MHC binding prediction.

BMC bioinformatics
BACKGROUND: Immunotherapy is an emerging approach in cancer treatment that activates the host immune system to destroy cancer cells expressing unique peptide signatures (neoepitopes). Administrations of cancer-specific neoepitopes in the form of synt...

Soft-sensing method based on FDLS-SVM in marine alkaline protease fermentation process.

Preparative biochemistry & biotechnology
To overcome the problem that soft-sensing model cannot be updated with the bioprocess changes, this article proposed a soft-sensing modeling method which combined fuzzy c-means clustering (FCM) algorithm with least squares support vector machine theo...

Multi-Path Dilated Residual Network for Nuclei Segmentation and Detection.

Cells
As a typical biomedical detection task, nuclei detection has been widely used in human health management, disease diagnosis and other fields. However, the task of cell detection in microscopic images is still challenging because the nuclei are common...

DEEPred: Automated Protein Function Prediction with Multi-task Feed-forward Deep Neural Networks.

Scientific reports
Automated protein function prediction is critical for the annotation of uncharacterized protein sequences, where accurate prediction methods are still required. Recently, deep learning based methods have outperformed conventional algorithms in comput...

Number detectors spontaneously emerge in a deep neural network designed for visual object recognition.

Science advances
Humans and animals have a "number sense," an innate capability to intuitively assess the number of visual items in a set, its numerosity. This capability implies that mechanisms to extract numerosity indwell the brain's visual system, which is primar...

Mobile Robot Path Planning Using Ant Colony Algorithm and Improved Potential Field Method.

Computational intelligence and neuroscience
For the problem of mobile robot's path planning under the known environment, a path planning method of mixed artificial potential field (APF) and ant colony optimization (ACO) based on grid map is proposed. First, based on the grid model, APF is impr...

Prediction of irinotecan toxicity in metastatic colorectal cancer patients based on machine learning models with pharmacokinetic parameters.

Journal of pharmacological sciences
Irinotecan (CPT-11) is a drug used against a wide variety of tumors, which can cause severe toxicity, possibly leading to the delay or suspension of the cycle, with the consequent impact on the prognosis of survival. The main goal of this work is to ...

Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithm.

Computers in biology and medicine
Recent analysis identified distinct genomic subtypes of lower-grade glioma tumors which are associated with shape features. In this study, we propose a fully automatic way to quantify tumor imaging characteristics using deep learning-based segmentati...

Prediction of hematoma expansion in spontaneous intracerebral hemorrhage using support vector machine.

EBioMedicine
BACKGROUND: Spontaneous intracerebral hemorrhage (ICH) is a devastating disease with high mortality rate. This study aimed to predict hematoma expansion in spontaneous ICH from routinely available variables by using support vector machine (SVM) metho...