[HTML][HTML] Computer-Aided Diagnosis Systems for Automatic Malaria Parasite Detection and Classification: A Systematic Review
Malaria is a disease that affects millions of people worldwide with a consistent mortality rate.
The light microscope examination is the gold standard for detecting infection by malaria …
The light microscope examination is the gold standard for detecting infection by malaria …
Potential diagnostic application of a novel deep learning-based approach for COVID-19
COVID-19 is a highly communicable respiratory illness caused by the novel coronavirus
SARS-CoV-2, which has had a significant impact on global public health and the economy …
SARS-CoV-2, which has had a significant impact on global public health and the economy …
An optimised YOLOv4 deep learning model for efficient malarial cell detection in thin blood smear images
Background Malaria is a serious public health concern worldwide. Early and accurate
diagnosis is essential for controlling the disease's spread and avoiding severe health …
diagnosis is essential for controlling the disease's spread and avoiding severe health …
Radiomics diagnostic performance for predicting lymph node metastasis in esophageal cancer: a systematic review and meta-analysis
D Ma, T Zhou, J Chen, J Chen - BMC Medical Imaging, 2024 - Springer
Background Esophageal cancer, a global health concern, impacts predominantly men,
particularly in Eastern Asia. Lymph node metastasis (LNM) significantly influences …
particularly in Eastern Asia. Lymph node metastasis (LNM) significantly influences …
CIA-CVD: cloud based image analysis for COVID-19 vaccination distribution
Due to the huge impact of COVID-19, the world is currently facing a medical emergency and
shortage of vaccine. Many countries do not have enough medical equipment and …
shortage of vaccine. Many countries do not have enough medical equipment and …
A critical analysis of transfer learning models for computer vision tasks
J Chhikara, N Goel, N Rathee - AIP Conference Proceedings, 2024 - pubs.aip.org
Transfer learning has proved to be a prominent tool in providing optimum results with limited
supervised data in various computer vision tasks. Despite the availability of many pre …
supervised data in various computer vision tasks. Despite the availability of many pre …
Possibilistic exponential spatial fuzzy clustering based cancer segmentation in multi-parametric prostate MRI
Cancer segmentation using multi-parametric prostate magnetic resonance imaging (mp-
MRI) is more opted by biomedical engineers and researchers because of its proven …
MRI) is more opted by biomedical engineers and researchers because of its proven …
DeepLeish: a deep learning based support system for the detection of Leishmaniasis parasite from Giemsa-stained microscope images
Background Leishmaniasis is a vector-born neglected parasitic disease belonging to the
genus Leishmania. Out of the 30 Leishmania species, 21 species cause human infection …
genus Leishmania. Out of the 30 Leishmania species, 21 species cause human infection …
Evaluation of deep learning-based reconstruction late gadolinium enhancement images for identifying patients with clinically unrecognized myocardial infarction
X Lu, WV Liu, Y Yan, W Yang, C Liu, W Gong… - BMC Medical …, 2024 - Springer
Background The presence of infarction in patients with unrecognized myocardial infarction
(UMI) is a critical feature in predicting adverse cardiac events. This study aimed to compare …
(UMI) is a critical feature in predicting adverse cardiac events. This study aimed to compare …
A Novel ODMC Model for Malaria Blood Smear Classification using Deep Feature Fusion and Optimization
Background: Malaria poses an enormous threat to humanity with ever increasing cases
annually. The research in the field of medical is contributing quite a lot in providing methods …
annually. The research in the field of medical is contributing quite a lot in providing methods …