AIMC Topic: Algorithms

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Prediction and Diagnosis of Breast Cancer Using Machine and Modern Deep Learning Models.

Asian Pacific journal of cancer prevention : APJCP
UNLABELLED: Background &Objective: Carcinoma of the breast is one of the major issues causing death in women, especially in developing countries. Timely prediction, detection, diagnosis, and efficient therapies have become critical to reducing death ...

A comparative study of CNN-capsule-net, CNN-transformer encoder, and Traditional machine learning algorithms to classify epileptic seizure.

BMC medical informatics and decision making
INTRODUCTION: Epilepsy is a disease characterized by an excessive discharge in neurons generally provoked without any external stimulus, known as convulsions. About 2 million people are diagnosed each year in the world. This process is carried out by...

Fast reconstruction of EEG signal compression sensing based on deep learning.

Scientific reports
When traditional EEG signals are collected based on the Nyquist theorem, long-time recordings of EEG signals will produce a large amount of data. At the same time, limited bandwidth, end-to-end delay, and memory space will bring great pressure on the...

An interpretable shapelets-based method for myocardial infarction detection using dynamic learning and deep learning.

Physiological measurement
Myocardial infarction (MI) is a prevalent cardiovascular disease that contributes to global mortality rates. Timely diagnosis and treatment of MI are crucial in reducing its fatality rate. Currently, electrocardiography (ECG) serves as the primary to...

Tracking mosquito-borne diseases via social media: a machine learning approach to topic modelling and sentiment analysis.

PeerJ
Mosquito-borne diseases (MBDs) are a major threat worldwide, and public consultation on these diseases is critical to disease control decision-making. However, traditional public surveys are time-consuming and labor-intensive and do not allow for tim...

Identification and segregation of genes with improved recurrent neural network trained with optimal gene level and mutation level features.

Computer methods in biomechanics and biomedical engineering
Even though many different approaches have been employed to address the complex mutational heterogeneity of cancer, finding driver genes is still problematic since other genomic factors cannot be fully integrated for combined analyses. This research ...

Development, validation, and transportability of several machine-learned, non-exercise-based VO prediction models for older adults.

Journal of sport and health science
BACKGROUND: There exist few maximal oxygen uptake (VO) non-exercise-based prediction equations, fewer using machine learning (ML), and none specifically for older adults. Since direct measurement of VO is infeasible in large epidemiologic cohort stud...

A comprehensive review on heart disease prognostication using different artificial intelligence algorithms.

Computer methods in biomechanics and biomedical engineering
Prediction of heart diseases on time is significant in order to preserve life. Many conventional methods have taken efforts on earlier prediction but faced with challenges of higher prediction cost, extended time for computation and complexities with...

A Hybrid Framework of Dual-Domain Signal Restoration and Multi-depth Feature Reinforcement for Low-Dose Lung CT Denoising.

Journal of imaging informatics in medicine
Low-dose computer tomography (LDCT) has been widely used in medical diagnosis. Various denoising methods have been presented to remove noise in LDCT scans. However, existing methods cannot achieve satisfactory results due to the difficulties in (1) d...