Artificial intelligence and machine learning assisted drug delivery for effective treatment of infectious diseases
In the era of antimicrobial resistance, the prevalence of multidrug-resistant microorganisms
that resist conventional antibiotic treatment has steadily increased. Thus, it is now …
that resist conventional antibiotic treatment has steadily increased. Thus, it is now …
A review of the machine learning algorithms for COVID-19 case analysis
The purpose of this article is to see how machine learning (ML) algorithms and applications
are used in the COVID-19 inquiry and for other purposes. The available traditional methods …
are used in the COVID-19 inquiry and for other purposes. The available traditional methods …
[HTML][HTML] Hybrid model for precise hepatitis-C classification using improved random forest and SVM method
Abstract Hepatitis C Virus (HCV) is a viral infection that causes liver inflammation. Annually,
approximately 3.4 million cases of HCV are reported worldwide. A diagnosis of HCV in …
approximately 3.4 million cases of HCV are reported worldwide. A diagnosis of HCV in …
[HTML][HTML] Hepatitis C Virus prediction based on machine learning framework: a real-world case study in Egypt
H Mamdouh Farghaly, MY Shams… - … and Information Systems, 2023 - Springer
Prediction and classification of diseases are essential in medical science, as it attempts to
immune the spread of the disease and discover the infected regions from the early stages …
immune the spread of the disease and discover the infected regions from the early stages …
[HTML][HTML] Intelligent system for COVID-19 prognosis: A state-of-the-art survey
This 21st century is notable for experiencing so many disturbances at economic, social,
cultural, and political levels in the entire world. The outbreak of novel corona virus 2019 …
cultural, and political levels in the entire world. The outbreak of novel corona virus 2019 …
A large-scale study of indicators of sub-clinical mastitis in dairy cattle by attribute weighting analysis of milk composition features: highlighting the predictive power of …
Sub-clinical mastitis (SCM) affects milk composition. In this study, we hypothesise that large-
scale mining of milk composition features by pattern recognition models can identify the best …
scale mining of milk composition features by pattern recognition models can identify the best …
[HTML][HTML] Survival prognostic factors in patients with acute myeloid leukemia using machine learning techniques
This paper identifies prognosis factors for survival in patients with acute myeloid leukemia
(AML) using machine learning techniques. We have integrated machine learning with …
(AML) using machine learning techniques. We have integrated machine learning with …
DrugMiner: comparative analysis of machine learning algorithms for prediction of potential druggable proteins
Highlights•Developing a novel machine learning tool for prediction of potential druggable
proteins.•Remarkable high performance of employed models in prediction.•Introducing new …
proteins.•Remarkable high performance of employed models in prediction.•Introducing new …
Hierarchical pattern recognition in milking parameters predicts mastitis prevalence
The aim of this study was to develop a predictive model for mastitis incidence, independent
from Somatic Cell Count (SCC), to provide an alternative, simple, and cost-effective …
from Somatic Cell Count (SCC), to provide an alternative, simple, and cost-effective …
Deep hyper optimization approach for disease classification using artificial intelligence
P Dhivya, A Bazilabanu - Data & Knowledge Engineering, 2023 - Elsevier
Abstract Disease classification using Artificial Intelligence (AI) is one of the emerging areas
for medical professionals to diagnose the disease. There are common diseases like breast …
for medical professionals to diagnose the disease. There are common diseases like breast …