The combination of convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to analyses patient data and medical images and makes the knowledge about how these models may be used to assist in the early diagnosis and pre-treatment plans.
The research introduces a dimension in which medical specialists can have real-time conversations with a trained LLM model that leverages knowledge from a medical encyclopedia, and enhances collaboration between AI and medical professionals, creating a platform for exchanging knowledge.
M. I. Ahmed· Journal of Intelligent Decis...· 1 citation
A physics-Informed Convolutional Neural Network for sort of brain tumour categorization from MRI images and followed by its testing framework to improve consistency and healthcare organizational adoption of deep learning frameworks is proposed.
Ayat Muthana, Zainab Mohammad Habeeb· Al-Noor Journal of Engineeri...· 0 citations
A classification model based on deep learning using a convolutional neural networks architecture, namely a 50-layer Residual Network (ResNet-50) using Gradient-weighted Class Activation Mapping (Grad-CAM) to provide improved automatic detection of renal pathology from medical images and improve the interpretability of...
L. Andrade-Arenas, Inooc Rubio Paucar, Cesar Yactayo-Arias· International Journal of Adv...· 0 citations
Empirical evidence from recent studies demonstrates that fine-tuning and network-based DTL strategies, including federated learning, consistently enhance diagnostic accuracy, robustness, and generalization across multiple medical imaging modalities, particularly in data-limited clinical scenarios.
M. A. S. Banu, A. Dhavapandiammal, K. Palanisamy· Current medical imaging· 0 citations
This comprehensive review systematically examines the architecture, functionality, and clinical effectiveness of ANN-based models applied to a diverse spectrum of medical imaging modalities, encompassing mammography, magnetic resonance imaging (MRI), computed tomography (CT), fundus photography, and dermoscopy.
Maryam Omar Al-Tohamy Abdel Hamid, A. Arjiah, Anaas Mansour Abdulsalam· Al-Farooq Journal of Science...· 0 citations
Lung cancer remains among the leading causes of mortality in the world and CT imaging is one of the crucial instruments of early diagnosis. These scans however are time consuming and prone to error in case they are manually interpreted. We use a dataset of 364 lung CT images in this study, as they have been obtained in...
Md Sujon Ali, M. Ahad, Fabiha Faiz Mahi et al.· 2026 International Conferenc...· 0 citations
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