ArticleJournal of medical systems2019
Multi-Class Neural Networks to Predict Lung Cancer.
Article in Journal of medical systems, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Cancer Risk Prediction Using Machine Learning for Supporting Early Cancer Diagnosis in Symptomatic Patients: A Systematic Review of Model Types.Cancer medicine · 2025Pooled it
- Combination of deep learning and ensemble machine learning using intraoperative video images strongly predicts recovery of urinary continence after robot-assisted radical prostatectomy.Cancer reports (Hoboken, N.J.) · 2023Article
- Deep learning model for multi-classification of infectious diseases from unstructured electronic medical records.BMC medical informatics and decision making · 2022Article
- A Dual-Network Modeling Architecture for Statistical Evaluation of College Graduates' Working Ability in Consistence with Their Job Position and Remuneration.Computational intelligence and neuroscience · 2022Article
- Fusion Evaluation of College Cultivation by Adaptive Multivariate Neural Network Model.Computational intelligence and neuroscience · 2022Article
- Article
- Lung Nodule Detection in CT Images Using Statistical and Shape-Based Features.Journal of imaging · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lung Cancer is the leading cause of death among all the cancers' in today's world. The survival rate of the patients is 85% if the cancer can be diagnosed during Stage 1. Mining of the patient records can help in diagnosing cancer during Stage 1. Using a multi-class neural networks helps to identify the disease during its stage 1 itself. The implementation of multi-class neural networks has yielded an accuracy of 100%. The model created using the neural networks approach helps to identify lung cancer during Stage 1 itself, thus the survival rate of the patients can be increased. This model can serve as pre-diagnosis tool for the practitioners.
Indexed as
Identifiers
31152236What OpenQuestion holds
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.