A comparative analysis of converters of tabular data into image for the classification of Arboviruses using Convolutional Neural Networks
L Medeiros Neto, S Rogerio da Silva Neto, PT Endo - Plos one, 2023 - journals.plos.org
Tabular data is commonly used in business and literature and can be analyzed using tree-
based Machine Learning (ML) algorithms to extract meaningful information. Deep Learning …
based Machine Learning (ML) algorithms to extract meaningful information. Deep Learning …
Everything is varied: The surprising impact of instantial variation on ML reliability
Instantial variation (IV) refers to variation that is due not to population differences or errors,
but rather to within-subject variation, that is the intrinsic and characteristic patterns of …
but rather to within-subject variation, that is the intrinsic and characteristic patterns of …
[PDF][PDF] An adaptive gradient boosting model for the prediction of rainfall using ID3 as a base estimator
Accepted: 4 April 2022 While analyzing the data, it is crucial to choose the model that best
matches the circumstance. Many experts in the field of classification and regression have …
matches the circumstance. Many experts in the field of classification and regression have …
[HTML][HTML] Prognostic prediction of left ventricular myocardial noncompaction using machine learning and cardiac magnetic resonance radiomics
PL Han, ZK Jiang, R Gu, S Huang, Y Jiang… - … Imaging in Medicine …, 2023 - ncbi.nlm.nih.gov
Background Although there are many studies on the prognostic factors of left ventricular
myocardial noncompaction (LVNC), the determinants are varied and not entirely consistent …
myocardial noncompaction (LVNC), the determinants are varied and not entirely consistent …
Big Data in Academia: A Proposed Framework for Improving Students Performance.
IR Banday, M Zaman, SMK Quadri… - Revue d' …, 2022 - search.ebscohost.com
The way people learn has radically changed as a result of information technology. As an
informal method of learning, fragmented learning has become a popular way to learn new …
informal method of learning, fragmented learning has become a popular way to learn new …
[PDF][PDF] How M5 Model Trees (M5-MT) on continuous data are used in rainfall prediction: An experimental evaluation
Accepted: 4 June 2022 When using machine learning to predict a class with a continuous
numeric value, there are several issues. Only a few machine-learning approaches are …
numeric value, there are several issues. Only a few machine-learning approaches are …
Integrated ensemble learning approach for multi-depth water quality estimation in reservoir environments
Water quality is paramount for the well-being of ecosystems and organisms, so assessing
water quality variables (WQVs) is imperative. Despite existing research on predicting WQVs …
water quality variables (WQVs) is imperative. Despite existing research on predicting WQVs …
Attention Res-UNet: Attention residual UNet with focal tversky loss for skin lesion segmentation
During a dermoscopy examination, accurate and automatic skin lesion detection and
segmentation can assist medical experts in resecting problematic areas and decrease the …
segmentation can assist medical experts in resecting problematic areas and decrease the …
[HTML][HTML] Deep learning-based multi-target regression for traffic-related air pollution forecasting
Traffic-related air pollution (TRAP) remains one of the main contributors to urban pollution
and its impact on climate change cannot be overemphasised. Experts in developed …
and its impact on climate change cannot be overemphasised. Experts in developed …
XMI-ICU: Explainable Machine Learning Model for Pseudo-Dynamic Prediction of Mortality in the ICU for Heart Attack Patients
Heart attack remain one of the greatest contributors to mortality in the United States and
globally. Patients admitted to the intensive care unit (ICU) with diagnosed heart attack …
globally. Patients admitted to the intensive care unit (ICU) with diagnosed heart attack …