Demystifying supervised learning in healthcare 4.0: A new reality of transforming diagnostic medicine
The global healthcare sector continues to grow rapidly and is reflected as one of the fastest-
growing sectors in the fourth industrial revolution (4.0). The majority of the healthcare …
growing sectors in the fourth industrial revolution (4.0). The majority of the healthcare …
A customized efficient deep learning model for the diagnosis of acute leukemia cells based on lymphocyte and monocyte images
S Ansari, AH Navin, AB Sangar, JV Gharamaleki… - Electronics, 2023 - mdpi.com
The production of blood cells is affected by leukemia, a type of bone marrow cancer or blood
cancer. Deoxyribonucleic acid (DNA) is related to immature cells, particularly white cells …
cancer. Deoxyribonucleic acid (DNA) is related to immature cells, particularly white cells …
Matradiomics: A novel and complete radiomics framework, from image visualization to predictive model
Radiomics aims to support clinical decisions through its workflow, which is divided into:(i)
target identification and segmentation,(ii) feature extraction,(iii) feature selection, and (iv) …
target identification and segmentation,(ii) feature extraction,(iii) feature selection, and (iv) …
An attention-based deep learning for acute lymphoblastic leukemia classification
The bone marrow overproduces immature cells in the malignancy known as Acute
Lymphoblastic Leukemia (ALL). In the United States, about 6500 occurrences of ALL are …
Lymphoblastic Leukemia (ALL). In the United States, about 6500 occurrences of ALL are …
An attention-based convolutional neural network for acute lymphoblastic leukemia classification
M Zakir Ullah, Y Zheng, J Song, S Aslam, C Xu… - Applied Sciences, 2021 - mdpi.com
Leukemia is a kind of blood cancer that influences people of all ages and is one of the
leading causes of death worldwide. Acute lymphoblastic leukemia (ALL) is the most widely …
leading causes of death worldwide. Acute lymphoblastic leukemia (ALL) is the most widely …
An automated liver tumour segmentation and classification model by deep learning based approaches
Liver cancer is regarded as one of the most common and leading causes of cancer death
around the world. Automatic liver tumour segmentation and classification techniques are …
around the world. Automatic liver tumour segmentation and classification techniques are …
A New Preclinical Decision Support System Based on PET Radiomics: A Preliminary Study on the Evaluation of an Innovative 64Cu-Labeled Chelator in Mouse …
The 64Cu-labeled chelator was analyzed in vivo by positron emission tomography (PET)
imaging to evaluate its biodistribution in a murine model at different acquisition times. For …
imaging to evaluate its biodistribution in a murine model at different acquisition times. For …
Per-COVID-19: a benchmark dataset for COVID-19 percentage estimation from CT-scans
COVID-19 infection recognition is a very important step in the fight against the COVID-19
pandemic. In fact, many methods have been used to recognize COVID-19 infection including …
pandemic. In fact, many methods have been used to recognize COVID-19 infection including …
COVIR: A virtual rendering of a novel NN architecture O-Net for COVID-19 Ct-scan automatic lung lesions segmentation
With the Coronavirus disease 2019 (COVID-19) spread, causing a world pandemic, and
recently, the virus new variants continue to appear, making the situation more challenging …
recently, the virus new variants continue to appear, making the situation more challenging …
Artificial Intelligence Applications on Restaging [18F]FDG PET/CT in Metastatic Colorectal Cancer: A Preliminary Report of Morpho-Functional Radiomics …
Featured Application Based on results defined in this study, new investigations might
propose morpho-functional-based radiomics algorithms for risk stratification with possible …
propose morpho-functional-based radiomics algorithms for risk stratification with possible …