[HTML][HTML] Deep self-supervised machine learning algorithms with a novel feature elimination and selection approaches for blood test-based multi-dimensional health …

O Tutsoy, GG Koç - BMC bioinformatics, 2024 - Springer
Background Blood test is extensively performed for screening, diagnoses and surveillance
purposes. Although it is possible to automatically evaluate the raw blood test data with the …

Peripheral blood smear analysis using deep learning: Current challenges and future directions

R Al–qudah, CY Suen - Computational Intelligence and Image …, 2022 - World Scientific
Despite the great advances in medicine in general, and hematology in specific, Peripheral
Blood Smear (PBS) remains as a key diagnostic test to both haematologists and physicians …

[HTML][HTML] Developing sustainable classification of diseases via deep learning and semi-supervised learning

C Yin, Z Chen - Healthcare, 2020 - mdpi.com
Disease classification based on machine learning has become a crucial research topic in
the fields of genetics and molecular biology. Generally, disease classification involves a …

[HTML][HTML] Prediction of -Thalassemia carriers using complete blood count features

F Rustam, I Ashraf, S Jabbar, K Tutusaus, C Mazas… - Scientific Reports, 2022 - nature.com
Abstract β-Thalassemia is one of the dangerous causes of the high mortality rate in the
Mediterranean countries. Substantial resources are required to save a β-Thalassemia …

A Survey on Peripheral Blood Smear Analysis Using Deep Learning

R Al-qudah, CY Suen - … Conference on Pattern Recognition and Artificial …, 2020 - Springer
Abstract Peripheral Blood Smear (PBS) analysis is a routine test carried out in specialized
medical laboratories by specialists to assess some aspects of health status that are …

Intensive Survey on Peripheral Blood Smear Analysis Using Deep Learning

R Alqudah, CY Suen - Advances in Pattern Recognition and …, 2022 - World Scientific
Peripheral Blood Smear (PBS) analysis is a routine test carried out in specialized medical
laboratories by specialists to assess some aspects of health status that are measured and …

[HTML][HTML] An artificial neural network approach and a data augmentation algorithm to systematize the diagnosis of deep-vein thrombosis by using wells' criteria

MB Fong-Mata, EE García-Guerrero, DA Mejía-Medina… - Electronics, 2020 - mdpi.com
The use of a back-propagation artificial neural network (ANN) to systematize the reliability of
a Deep Vein Thrombosis (DVT) diagnostic by using Wells' criteria is introduced herein. In …

Integration of unsupervised and supervised machine learning algorithms for credit risk assessment

W Bao, N Lianju, K Yue - Expert Systems with Applications, 2019 - Elsevier
For the sake of credit risk assessment, credit scoring has become a critical tool to
discriminate “bad” applicants from “good” applicants for financial institutions. Accordingly, a …

[PDF][PDF] Automated white blood cell disease recognition using lightweight deep learning

A Alqahtani, S Alsubai, M Sha, MA Khan, M Alhaisoni… - reactions, 2023 - researchgate.net
White blood cells (WBC) are immune system cells, which is why they are also known as
immune cells. They protect the human body from a variety of dangerous diseases and …

[PDF][PDF] Classification of white blood cells by deep learning methods for diagnosing disease.

M Yildirim, A Çinar - Rev. d'Intelligence Artif., 2019 - researchgate.net
Accepted: 29 August 2019 Leukocytes, also known as white blood cells, are a group of cells
that protect the body against infections, which is an important part of the immune system …