Olive disease classification based on vision transformer and CNN models
It has been noted that disease detection approaches based on deep learning are becoming
increasingly important in artificial intelligence‐based research in the field of agriculture …
increasingly important in artificial intelligence‐based research in the field of agriculture …
Parallel multi-head attention and term-weighted question embedding for medical visual question answering
The goal of medical visual question answering (Med-VQA) is to correctly answer a clinical
question posed by a medical image. Medical images are fundamentally different from …
question posed by a medical image. Medical images are fundamentally different from …
Machine learning algorithm accuracy using single-versus multi-institutional image data in the classification of prostate MRI lesions
D Provenzano, O Melnyk, D Imtiaz, B McSweeney… - Applied Sciences, 2023 - mdpi.com
Featured Application The purpose of this study was to determine the efficacy of highly
accurate ML classification algorithms trained on prostate image data from one institution and …
accurate ML classification algorithms trained on prostate image data from one institution and …
Medical text classification based on an optimized machine learning and external semantic resource
K Gasmi - Journal of circuits, systems and computers, 2022 - World Scientific
Automatic classification of texts is a well-known topic in natural language processing (NLP),
and it involves categorizing unstructured texts into specific groups. Classification algorithms …
and it involves categorizing unstructured texts into specific groups. Classification algorithms …
Visual question answering on blood smear images using convolutional block attention module powered object detection
One of the vital characteristics that determine the health condition of a person is the shape
and number of the red blood cells, white blood cells and platelets present in one's blood …
and number of the red blood cells, white blood cells and platelets present in one's blood …
Investigating the impact of pretraining corpora on the performance of Arabic BERT models
AS Alammary - The Journal of Supercomputing, 2025 - Springer
Abstract Bidirectional Encoder Representations from Transformers (BERT), a revolutionary
model in natural language processing (NLP), has significantly impacted text-related tasks …
model in natural language processing (NLP), has significantly impacted text-related tasks …
Improving bert-based model for medical text classification with an optimization algorithm
K Gasmi - International Conference on Computational Collective …, 2022 - Springer
In the field of Natural Language Processing (NLP), automatic text classification is a classic
topic that involves classifying textual material into predetermined categories based on its …
topic that involves classifying textual material into predetermined categories based on its …
A Review on Deep Learning Based Question Answering with Natural Language Processing in Healthcare
AS Javeed, CG Krishnan - 2024 International Conference on …, 2024 - ieeexplore.ieee.org
Over the Internet, an efficient approach and promising solution to retrieve significant
information envisages the beginning of Question Answering Systems (QAS). Because of …
information envisages the beginning of Question Answering Systems (QAS). Because of …
Cataract Disease Identification Using Transformer and Convolution Neural Network: A Novel Framework
The significance of disease detection approaches based on deep learning (DL) in medical
research, driven by artificial intelligence (AI), is gaining considerable attention. However …
research, driven by artificial intelligence (AI), is gaining considerable attention. However …
Explainable AI for Medical Imaging: Advancing Transparency and Trust in Diagnostic Decision-Making
Osteoarthritis (OA) is an existing degenerative joint disease with a potential societal impact,
requiring accurate and early diagnosis for effective treatment. In this work, we have …
requiring accurate and early diagnosis for effective treatment. In this work, we have …