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[HTML][HTML] A machine learning approach for micro-credit scoring
In micro-lending markets, lack of recorded credit history is a significant impediment to
assessing individual borrowers' creditworthiness and therefore deciding fair interest rates …
assessing individual borrowers' creditworthiness and therefore deciding fair interest rates …
[HTML][HTML] Evaluating the Impact of Recursive Feature Elimination on Machine Learning Models for Predicting Forest Fire-Prone Zones
This study aimed to enhance the accuracy of forest fire susceptibility map** (FSM) by
innovatively applying recursive feature elimination (RFE) with an ensemble of machine …
innovatively applying recursive feature elimination (RFE) with an ensemble of machine …
A Novel Ensemble‐Based Technique for the Preemptive Diagnosis of Rheumatoid Arthritis Disease in the Eastern Province of Saudi Arabia Using Clinical Data
Rheumatoid arthritis (RA) is a chronic inflammatory disease caused by numerous genetic
and environmental factors leading to musculoskeletal system pain. RA may damage other …
and environmental factors leading to musculoskeletal system pain. RA may damage other …
Clinical assessment of diabetic foot ulcers using GWO-CNN based hyperspectral image processing approach
T Arumuga Maria Devi, R Hepzibai - IETE Journal of Research, 2023 - Taylor & Francis
Diabetes Mellitus has turned out to be a complicated disease and as of 2016 one out of
eleven humans suffer from this disease leading to Diabetic Foot Ulcers (DFU). When not …
eleven humans suffer from this disease leading to Diabetic Foot Ulcers (DFU). When not …
A Comparative Study of Feature Extraction Methods in Image Classification Using Convolution Neural Network Model
Image classification is the supervised classification in which one assigns labels to images
based on its characteristics or features. The term Outlier which is also referred as anomaly …
based on its characteristics or features. The term Outlier which is also referred as anomaly …
COVID-19 vaccination performance of the US states: a hybrid model of DEA and ensemble machine learning methods
Vaccination is seen as the most promising one among the efforts to stop COVID-19 and the
US government has given great importance to vaccination. However, which states have …
US government has given great importance to vaccination. However, which states have …
[PDF][PDF] A Machine Learning Approach for Micro-Credit Scoring. Risks, 9 (3), 50
A Ampountolas, TN Nde, P Date, C Constantinescu - 2021 - academia.edu
In micro-lending markets, lack of recorded credit history is a significant impediment to
assessing individual borrowers' creditworthiness and therefore deciding fair interest rates …
assessing individual borrowers' creditworthiness and therefore deciding fair interest rates …
Machine Learning Model for Predicting Hepatocellular Carcinoma in Hepatitis C Patients
A Fatima, J Andritsch - 2024 2nd International Conference on …, 2024 - ieeexplore.ieee.org
An estimated 58 million people suffer from chronic Hepatitis C virus around the world, while
substantial evidence indicates that patients with Hepatitis C virus are at 17 times larger risk …
substantial evidence indicates that patients with Hepatitis C virus are at 17 times larger risk …
Artificial intelligence based diagnostic model for the detection of malaria parasites from microscopic blood images
Background. Malaria is a severe infectious disease that is caused by protozoa of the genus
Plasmodium. Manual identification of parasites in microscopic blood image examination …
Plasmodium. Manual identification of parasites in microscopic blood image examination …
Parasites from Microscopic Blood Images
G Madhu, A Govardhan - Intelligent Interactive Multimedia …, 2021 - books.google.com
Malaria is a severe global health issue that causes morbidity and mortality of vectorborne
disease that is caused by a Plasmodium parasite of the genus Plasmodium, as declared by …
disease that is caused by a Plasmodium parasite of the genus Plasmodium, as declared by …