AI Medical Compendium Journal:
Computational and mathematical methods in medicine

Showing 21 to 30 of 406 articles

An Unsupervised Deep Learning-Based Model Using Multiomics Data to Predict Prognosis of Patients with Stomach Adenocarcinoma.

Computational and mathematical methods in medicine
METHODS: Patients (363 in total) with stomach adenocarcinoma from The Cancer Genome Atlas (TCGA) cohort were included. An autoencoder was constructed to integrate the RNA sequencing, miRNA sequencing, and methylation data. The features of the bottlen...

Finger Vein Verification on Different Datasets Based on Deep Learning with Triplet Loss.

Computational and mathematical methods in medicine
In this study, deep learning and triplet loss function methods are used for finger vein verification research, and the model is trained and validated between different kinds of datasets including FV-USM, HKPU, and SDUMLA-HMT datasets. This work gives...

Deep Transfer Learning for COVID-19 Detection and Lesion Recognition Using Chest CT Images.

Computational and mathematical methods in medicine
Starting from December 2019, the global pandemic of coronavirus disease 2019 (COVID-19) is continuously expanding and has caused several millions of deaths worldwide. Fast and accurate diagnostic methods for COVID-19 detection play a vital role in co...

Analysis of Characteristic Factors of Nursing Safety Incidents in ENT Surgery by Deep Learning-Based Medical Data Association Rules Method.

Computational and mathematical methods in medicine
It is of great significance to explore the characteristic factors of postoperative nursing safety events in patients with otolaryngology surgery and to understand the characteristics of postoperative nursing safety events in otolaryngology surgery pa...

The Association of Waist Circumference with the Prevalence and Survival of Digestive Tract Cancer in US Adults: A Population Study Based on Machine Learning Methods.

Computational and mathematical methods in medicine
AIMS: This paper aims to investigate the relationship of waist circumference (WC) with digestive tract cancer morbidity and mortality.

MHA-Net: A Multibranch Hybrid Attention Network for Medical Image Segmentation.

Computational and mathematical methods in medicine
The robust segmentation of organs from the medical image is the key technique in medical image analysis for disease diagnosis. U-Net is a robust structure for medical image segmentation. However, U-Net adopts consecutive downsampling encoders to capt...

A Classification Method for Thoracolumbar Vertebral Fractures due to Basketball Sports Injury Based on Deep Learning.

Computational and mathematical methods in medicine
OBJECTIVE: There are more and more basketball competitions, to propose a classification method of thoracolumbar fractures to assist in the diagnosis of basketball injuries, to analyze the feasibility of its clinical application, and to improve the re...

Breast MRI Segmentation and Ki-67 High- and Low-Expression Prediction Algorithm Based on Deep Learning.

Computational and mathematical methods in medicine
RESULTS: The DSC, PPV, and sensitivity of our combined model are 0.94, 0.93, and 0.94, respectively, with better segmentation performance. And we compare with the segmentation frameworks of other papers and find that our combined model can make accur...

Predicting Conserved Water Molecules in Binding Sites of Proteins Using Machine Learning Methods and Combining Features.

Computational and mathematical methods in medicine
Water molecules play an important role in many biological processes in terms of stabilizing protein structures, assisting protein folding, and improving binding affinity. It is well known that, due to the impacts of various environmental factors, it ...

Neural Networks for Survival Prediction in Medicine Using Prognostic Factors: A Review and Critical Appraisal.

Computational and mathematical methods in medicine
Survival analysis deals with the expected duration of time until one or more events of interest occur. Time to the event of interest may be unobserved, a phenomenon commonly known as right censoring, which renders the analysis of these data challengi...