[HTML][HTML] PLDPNet: End-to-end hybrid deep learning framework for potato leaf disease prediction
Agricultural productivity plays a vital role in global economic development and growth. When
crops are affected by diseases, it adversely impacts a nation's economic resources and …
crops are affected by diseases, it adversely impacts a nation's economic resources and …
Hybrid techniques for the diagnosis of acute lymphoblastic leukemia based on fusion of CNN features
Acute lymphoblastic leukemia (ALL) is one of the deadliest forms of leukemia due to the
bone marrow producing many white blood cells (WBC). ALL is one of the most common …
bone marrow producing many white blood cells (WBC). ALL is one of the most common …
A hybrid lightweight breast cancer classification framework using the histopathological images
D Addo, S Zhou, K Sarpong, OT Nartey… - Biocybernetics and …, 2024 - Elsevier
A crucial element in the diagnosis of breast cancer is the utilization of a classification method
that is efficient, lightweight, and precise. Convolutional neural networks (CNNs) have …
that is efficient, lightweight, and precise. Convolutional neural networks (CNNs) have …
Automatic classification of colour fundus images for prediction eye disease types based on hybrid features
A Shamsan, EM Senan, HSA Shatnawi - Diagnostics, 2023 - mdpi.com
Early detection of eye diseases is the only solution to receive timely treatment and prevent
blindness. Colour fundus photography (CFP) is an effective fundus examination technique …
blindness. Colour fundus photography (CFP) is an effective fundus examination technique …
Advancements and Prospects of Machine Learning in Medical Diagnostics: Unveiling the Future of Diagnostic Precision
S Asif, Y Wenhui, S ur-Rehman, Q ul-ain… - … Methods in Engineering, 2024 - Springer
Abstract Machine learning (ML) has emerged as a versatile and powerful tool in various
fields of medicine, revolutionizing early disease diagnosis, particularly in cases where …
fields of medicine, revolutionizing early disease diagnosis, particularly in cases where …
Building ensemble of deep networks: convolutional networks and transformers
This paper presents a study on an automated system for image classification, which is based
on the fusion of various deep learning methods. The study explores how to create an …
on the fusion of various deep learning methods. The study explores how to create an …
Deep learning myocardial infarction segmentation framework from cardiac magnetic resonance images
Segmentation of myocardial infarction (MI) is a crucial task in the field of heart disease
theranostics. Cardiac magnetic resonance imaging (MRI) is a well-known non-invasive …
theranostics. Cardiac magnetic resonance imaging (MRI) is a well-known non-invasive …
Blood slide image analysis to classify WBC types for prediction haematology based on a hybrid model of CNN and handcrafted features
White blood cells (WBCs) are one of the main components of blood produced by the bone
marrow. WBCs are part of the immune system that protects the body from infectious diseases …
marrow. WBCs are part of the immune system that protects the body from infectious diseases …
Analysis of histopathological images for early diagnosis of oral squamous cell carcinoma by hybrid systems based on CNN fusion features
Oral squamous cell carcinoma (OSCC) is one of the deadliest and most common types of
cancer. The incidence of OSCC is increasing annually, which requires early diagnosis to …
cancer. The incidence of OSCC is increasing annually, which requires early diagnosis to …
Comparative analysis of artificial intelligence for predicting covid-19 using diverse chest x-ray images
COVID-19 prediction plays a crucial role in medical decision-making for respiratory health.
Accurate and rapid prediction using advanced artificial intelligence (AI) techniques is …
Accurate and rapid prediction using advanced artificial intelligence (AI) techniques is …