ReviewBioengineered
Biologically inspired intelligent decision making: a commentary on the use of artificial neural networks in bioinformatics.
Review in Bioengineered. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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
21 citing papers in PubMed.
- Dynamic changes of intestinal flora in patients with irritable bowel syndrome combined with anxiety and depression after oral administration of enterobacteria capsules.Bioengineered · 2021Trial
- Exploring the efficacy of artificial neural networks in predicting lung cancer recurrence: a retrospective study based on patient records.Translational lung cancer research · 2023Article
- Machine learning predicts clinically significant health related quality of life improvement after sensorimotor rehabilitation interventions in chronic stroke.Scientific reports · 2022Article
- Artificial Intelligence-Driven Prediction Modeling and Decision Making in Spine Surgery Using Hybrid Machine Learning Models.Journal of personalized medicine · 2022Review
- Accuracy of Ultrasound Diagnosis of Thyroid Nodules Based on Artificial Intelligence-Assisted Diagnostic Technology: A Systematic Review and Meta-Analysis.International journal of endocrinology · 2022Article
- An Artificial Neural Network Prediction Model for Posttraumatic Epilepsy: Retrospective Cohort Study.Journal of medical Internet research · 2021Article
- Sequential Pattern Mining to Predict Medical In-Hospital Mortality from Administrative Data: Application to Acute Coronary Syndrome.Journal of healthcare engineering · 2021Article
- Predicting clinically significant motor function improvement after contemporary task-oriented interventions using machine learning approaches.Journal of neuroengineering and rehabilitation · 2020Article
- Article
- Dental Caries Prediction Based on a Survey of the Oral Health Epidemiology among the Geriatric Residents of Liaoning, China.BioMed research international · 2020Article
- Artificial Intelligence for Personalized Medicine in Thyroid Cancer: Current Status and Future Perspectives.Frontiers in oncology · 2020Review
- Article
- Motor Skills as Moderators of Core Symptoms in Autism Spectrum Disorders: Preliminary Data From an Exploratory Analysis With Artificial Neural Networks.Frontiers in psychology · 2018Article
- Mortality prediction in patients with isolated moderate and severe traumatic brain injury using machine learning models.PloS one · 2018Article
- Nodular Thyroid Disease and Thyroid Cancer in the Era of Precision Medicine.European thyroid journal · 2017Review
- Sequence homolog-based molecular engineering for shifting the enzymatic pH optimum.Synthetic and systems biotechnology · 2016Article
- The importance of physicochemical characteristics and nonlinear classifiers in determining HIV-1 protease specificity.Bioengineered · 2016Article
- Prediction of Clinical Deterioration in Hospitalized Adult Patients with Hematologic Malignancies Using a Neural Network Model.PloS one · 2016Article
- The optimization of Marasmius androsaceus submerged fermentation conditions in five-liter fermentor.Saudi journal of biological sciences · 2016Article
- Predicting outcomes in patients with perforated gastroduodenal ulcers: artificial neural network modelling indicates a highly complex disease.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2015Observational
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
Artificial neural networks (ANNs) are a class of powerful machine learning models for classification and function approximation which have analogs in nature. An ANN learns to map stimuli to responses through repeated evaluation of exemplars of the mapping. This learning approach results in networks which are recognized for their noise tolerance and ability to generalize meaningful responses for novel stimuli. It is these properties of ANNs which make them appealing for applications to bioinformatics problems where interpretation of data may not always be obvious, and where the domain knowledge required for deductive techniques is incomplete or can cause a combinatorial explosion of rules. In this paper, we provide an introduction to artificial neural network theory and review some interesting recent applications to bioinformatics problems.
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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.