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An idiosyncratic MIMBO-NBRF based automated system for child birth mode prediction.
Publication Type: Academic Journal
Source(s): Artificial intelligence in medicine [Artif Intell Med] 2023 Sep; Vol. 143, pp. 102621. Date of Electronic Publication: 2023 Jul 05.
Abstract: Predicting the mode of child birth is still remains one of the most complex and challenging tasks in ancient times. Also, there is no such strong methodologies are developed in the conventional works for birth mode prediction. Therefore, the proposed w...
Individual risk prediction: Comparing random forests with Cox proportional-hazards model by a simulation study.
Publication Type: Academic Journal
Source(s): Biometrical journal. Biometrische Zeitschrift [Biom J] 2023 Aug; Vol. 65 (6), pp. e2100380. Date of Electronic Publication: 2022 Sep 28.
Abstract: With big data becoming widely available in healthcare, machine learning algorithms such as random forest (RF) that ignores time-to-event information and random survival forest (RSF) that handles right-censored data are used for individual risk predicti...
A Random Forest Model for Peptide Classification Based on Virtual Docking Data.
Publication Type: Academic Journal
Source(s): International journal of molecular sciences [Int J Mol Sci] 2023 Jul 13; Vol. 24 (14). Date of Electronic Publication: 2023 Jul 13.
Abstract: The affinity of peptides is a crucial factor in studying peptide-protein interactions. Despite the development of various techniques to evaluate peptide-receptor affinity, the results may not always reflect the actual affinity of the peptides accuratel...
Which are best for successful aging prediction? Bagging, boosting, or simple machine learning algorithms?
Publication Type: Academic Journal
Source(s): Biomedical engineering online [Biomed Eng Online] 2023 Aug 29; Vol. 22 (1), pp. 85. Date of Electronic Publication: 2023 Aug 29.
Abstract: Background: The worldwide society is currently facing an epidemiological shift due to the significant improvement in life expectancy and increase in the elderly population. This shift requires the public and scientific community to highlight successful...
A new method for fault identification of T-connection transmission line based on multi-scale traveling wave reactive power and random forest.
Publication Type: Academic Journal
Source(s): PloS one [PLoS One] 2023 Aug 18; Vol. 18 (8), pp. e0284937. Date of Electronic Publication: 2023 Aug 18 (Print Publication: 2023).
Abstract: Though the traditional fault diagnosis method of T-connected transmission lines can identify the faults inside and outside the area, it can not identify the specific branches. To improve the accuracy and reliability of fault diagnosis of T-connection t...
Immune cell type signature discovery and random forest classification for analysis of single cell gene expression datasets.
Publication Type: Academic Journal
Source(s): Frontiers in immunology [Front Immunol] 2023 Aug 04; Vol. 14, pp. 1194745. Date of Electronic Publication: 2023 Aug 04 (Print Publication: 2023).
Abstract: Background: Robust immune cell gene expression signatures are central to the analysis of single cell studies. Nearly all known sets of immune cell signatures have been derived by making use of only single gene expression datasets. Utilizing the power o...
Time series causal relationships discovery through feature importance and ensemble models.
Publication Type: Academic Journal
Source(s): Scientific reports [Sci Rep] 2023 Jul 14; Vol. 13 (1), pp. 11402. Date of Electronic Publication: 2023 Jul 14.
Abstract: Inferring causal relationships from observational data is a key challenge in understanding the interpretability of Machine Learning models. Given the ever-increasing amount of observational data available in many areas, Machine Learning algorithms used...
Buckley-James boosting model based on extreme learning machine and random survival forests.
Publication Type: Academic Journal
Source(s): Biometrical journal. Biometrische Zeitschrift [Biom J] 2023 Jun; Vol. 65 (5), pp. e2200153. Date of Electronic Publication: 2023 Apr 17.
Abstract: Buckley-James (BJ) model is a typical semiparametric accelerated failure time model, which is closely related to the ordinary least squares method and easy to be constructed. However, traditional BJ model built on linearity assumption only captures sim...
Urine output as one of the most important features in differentiating in-hospital death among patients receiving extracorporeal membrane oxygenation: a random forest approach.
Publication Type: Academic Journal
Source(s): European journal of medical research [Eur J Med Res] 2023 Sep 15; Vol. 28 (1), pp. 347. Date of Electronic Publication: 2023 Sep 15.
Abstract: Background: It is common to support cardiovascular function in critically ill patients with extracorporeal membrane oxygenation (ECMO). The purpose of this study was to identify patients receiving ECMO with a considerable risk of dying in hospital usin...
Exploring the variable importance in random forests under correlations: a general concept applied to donor organ quality in post-transplant survival.
Publication Type: Academic Journal
Source(s): BMC medical research methodology [BMC Med Res Methodol] 2023 Sep 19; Vol. 23 (1), pp. 209. Date of Electronic Publication: 2023 Sep 19.
Abstract: Random Forests are a powerful and frequently applied Machine Learning tool. The permutation variable importance (VIMP) has been proposed to improve the explainability of such a pure prediction model. It describes the expected increase in prediction err...