Machine learning approaches in microbiome research: challenges and best practices
Microbiome data predictive analysis within a machine learning (ML) workflow presents
numerous domain-specific challenges involving preprocessing, feature selection, predictive …
numerous domain-specific challenges involving preprocessing, feature selection, predictive …
A review on variable selection in regression analysis
LDD Desboulets - Econometrics, 2018 - mdpi.com
In this paper, we investigate several variable selection procedures to give an overview of the
existing literature for practitioners.“Let the data speak for themselves” has become the motto …
existing literature for practitioners.“Let the data speak for themselves” has become the motto …
Bootstrapping the out-of-sample predictions for efficient and accurate cross-validation
I Tsamardinos, E Greasidou, G Borboudakis - Machine learning, 2018 - Springer
Abstract Cross-Validation (CV), and out-of-sample performance-estimation protocols in
general, are often employed both for (a) selecting the optimal combination of algorithms and …
general, are often employed both for (a) selecting the optimal combination of algorithms and …
Bias and fairness assessment of a natural language processing opioid misuse classifier: detection and mitigation of electronic health record data disadvantages …
HM Thompson, B Sharma, S Bhalla… - Journal of the …, 2021 - academic.oup.com
Objectives To assess fairness and bias of a previously validated machine learning opioid
misuse classifier. Materials & Methods Two experiments were conducted with the classifier's …
misuse classifier. Materials & Methods Two experiments were conducted with the classifier's …
An efficient machine learning approach for diagnosis of paraquat-poisoned patients
L Hu, G Hong, J Ma, X Wang, H Chen - Computers in Biology and Medicine, 2015 - Elsevier
Numerous people die of paraquat (PQ) poisoning because they were not diagnosed and
treated promptly at an early stage. Till now, determination of PQ levels in blood or urine is …
treated promptly at an early stage. Till now, determination of PQ levels in blood or urine is …
Validating hyperspectral image segmentation
Hyperspectral satellite imaging attracts enormous research attention in the remote sensing
community, and hence, automated approaches for precise segmentation of such imagery …
community, and hence, automated approaches for precise segmentation of such imagery …
Empirical study of seven data mining algorithms on different characteristics of datasets for biomedical classification applications
Y Zhang, Y Xin, Q Li, J Ma, S Li, X Lv, W Lv - Biomedical engineering …, 2017 - Springer
Background Various kinds of data mining algorithms are continuously raised with the
development of related disciplines. The applicable scopes and their performances of these …
development of related disciplines. The applicable scopes and their performances of these …
A machine learning framework to predict antibiotic resistance traits and yet unknown genes underlying resistance to specific antibiotics in bacterial strains
Recently, the frequency of observing bacterial strains without known genetic components
underlying phenotypic resistance to antibiotics has increased. There are several strains of …
underlying phenotypic resistance to antibiotics has increased. There are several strains of …
Don't lose samples to estimation
I Tsamardinos - Patterns, 2022 - cell.com
In a typical predictive modeling task, we are asked to produce a final predictive model to
employ operationally for predictions, as well as an estimate of its out-of-sample predictive …
employ operationally for predictions, as well as an estimate of its out-of-sample predictive …
Block forests: random forests for blocks of clinical and omics covariate data
Background In the last years more and more multi-omics data are becoming available, that
is, data featuring measurements of several types of omics data for each patient. Using multi …
is, data featuring measurements of several types of omics data for each patient. Using multi …