ArticleCluster computing2023
Popular deep learning algorithms for disease prediction: a review.
Article in Cluster computing, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
20 citing papers in PubMed.
- CardioMetaHybridOptimizer as a behaviorally adaptive multi-phase metaheuristic framework for interpretable cardiovascular disease diagnosis.BMC bioinformatics · 2026Article
- Analysis of Models to Estimate Morbidity Rates of Respiratory Diseases Through Deep Learning.Tropical medicine & international health : TM & IH · 2026Article
- Toward accurate prediction of pediatric epidemic disease patient volume in the Chaoshan region: A deep learning framework.iScience · 2026Article
- Alzheimer's disease classification using mutual information generated graph convolutional network for functional MRI.Journal of Alzheimer's disease : JAD · 2025Article
- Automated Risk Prediction of Post-Stroke Adverse Mental Outcomes Using Deep Learning Methods and Sequential Data.Bioengineering (Basel, Switzerland) · 2025Article
- Optimizing the dynamic treatment regime of outpatient rehabilitation in patients with knee osteoarthritis using reinforcement learning.Journal of neuroengineering and rehabilitation · 2025Article
- Optimized Machine Learning for the Early Detection of Polycystic Ovary Syndrome in Women.Sensors (Basel, Switzerland) · 2025Article
- An Ensemble Machine Learning Model for Early Prediction of Vancomycin-Induced Acute Kidney Injury in ICU Patients.Archives of academic emergency medicine · 2025Article
- Review
- EPheClass: ensemble-based phenotype classifier from 16S rRNA gene sequences.Frontiers in bioinformatics · 2025Article
- Explainable artificial intelligence for stroke prediction through comparison of deep learning and machine learning models.Scientific reports · 2024Article
- Electroencephalography-based classification of Alzheimer's disease spectrum during computer-based cognitive testing.Scientific reports · 2024Article
- Radiologic Technology Students' Perceptions on Adoption of Artificial Intelligence Technology in Radiology.International journal of general medicine · 2024Article
- Article
- Leveraging AI to improve disease screening among American Indians: insights from the Strong Heart Study.Experimental biology and medicine (Maywood, N.J.) · 2024Article
- Breast Cancer Classification Using Synthesized Deep Learning Model with Metaheuristic Optimization Algorithm.Diagnostics (Basel, Switzerland) · 2023Article
- Design and Validation of a Deep Learning Model for Renal Stone Detection and Segmentation on Kidney-Ureter-Bladder Images.Bioengineering (Basel, Switzerland) · 2023Article
- A comprehensive systematic and bibliometric review of the IoT-based healthcare systems.Cluster computing · 2023Review
- Article
- A review of multi-omics data integration through deep learning approaches for disease diagnosis, prognosis, and treatment.Frontiers in genetics · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Due to its automatic feature learning ability and high performance, deep learning has gradually become the mainstream of artificial intelligence in recent years, playing a role in many fields. Especially in the medical field, the accuracy rate of deep learning even exceeds that of doctors. This paper introduces several deep learning algorithms: Artificial Neural Network (NN), FM-Deep Learning, Convolutional NN and Recurrent NN, and expounds their theory, development history and applications in disease prediction; we analyze the defects in the current disease prediction field and give some current solutions; our paper expounds the two major trends in the future disease prediction and medical field-integrating Digital Twins and promoting precision medicine. This study can better inspire relevant researchers, so that they can use this article to understand related disease prediction algorithms and then make better related research.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.