Deep transfer learning approaches for Monkeypox disease diagnosis
Monkeypox has become a significant global challenge as the number of cases increases
daily. Those infected with the disease often display various skin symptoms and can spread …
daily. Those infected with the disease often display various skin symptoms and can spread …
Harnessing of artificial intelligence for the diagnosis and prevention of hospital-acquired infections: a systematic review
B Baddal, F Taner, D Uzun Ozsahin - Diagnostics, 2024 - mdpi.com
Healthcare-associated infections (HAIs) are the most common adverse events in healthcare
and constitute a major global public health concern. Surveillance represents the foundation …
and constitute a major global public health concern. Surveillance represents the foundation …
Towards digital diagnosis of malaria: How far have we reached?
S Aqeel, Z Haider, W Khan - Journal of Microbiological Methods, 2023 - Elsevier
The need for precise and early diagnosis of malaria and its distinction from other febrile
illnesses is no doubt a prerequisite, primarily when standard rapid diagnostic tests (RDTs) …
illnesses is no doubt a prerequisite, primarily when standard rapid diagnostic tests (RDTs) …
Autokeras approach: A robust automated deep learning network for diagnosis disease cases in medical images
Automated deep learning is promising in artificial intelligence (AI). However, a few
applications of automated deep learning networks have been made in the clinical medical …
applications of automated deep learning networks have been made in the clinical medical …
Deep hybrid model for Mpox disease diagnosis from skin lesion images
This research presents DNLR‐NET, a novel model designed for automated and accurate
diagnosis of MPox disease. The model's performance is constructed and validated using a …
diagnosis of MPox disease. The model's performance is constructed and validated using a …
An optimized features selection approach based on Manta Ray Foraging Optimization (MRFO) method for parasite malaria classification
J Amin, M Sharif, GA Mallah… - Frontiers in Public Health, 2022 - frontiersin.org
Malaria is a serious and lethal disease that has been reported by the World Health
Organization (WHO), with an estimated 219 million new cases and 435,000 deaths globally …
Organization (WHO), with an estimated 219 million new cases and 435,000 deaths globally …
[HTML][HTML] Deep learning algorithms for efficient analysis of ecg signals to detect heart disorders
Electrocardiography (ECG) has been a reliable method for monitoring the proper functioning
of the cardiovascular system for decades. Recently, there has been a lot of research …
of the cardiovascular system for decades. Recently, there has been a lot of research …
Paving the way: contributions of big data to apicomplexan and kinetoplastid research
In the age of big data an important question is how to ensure we make the most out of the
resources we generate. In this review, we discuss the major methods used in Apicomplexan …
resources we generate. In this review, we discuss the major methods used in Apicomplexan …
[HTML][HTML] Machine learning for predicting Plasmodium liver stage development in vitro using microscopy imaging
CF Otesteanu, R Caldelari, V Heussler… - Computational and …, 2024 - Elsevier
Malaria, a significant global health challenge, is caused by Plasmodium parasites. The
Plasmodium liver stage plays a pivotal role in the establishment of the infection. This study …
Plasmodium liver stage plays a pivotal role in the establishment of the infection. This study …
Embedded System‐Based Malaria Detection From Blood Smear Images Using Lightweight Deep Learning Model
The disease of malaria, transmitted by female Anopheles mosquitoes, is highly contagious,
resulting in numerous deaths across various regions. Microscopic examination of blood cells …
resulting in numerous deaths across various regions. Microscopic examination of blood cells …