AIMC Topic: Diagnosis, Computer-Assisted

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SeLa-MIL: Developing an instance-level classifier via weakly-supervised self-training for whole slide image classification.

Computer methods and programs in biomedicine Jan 27, 2025
BACKGROUND AND OBJECTIVE: Pathology image classification is crucial in clinical cancer diagnosis and computer-aided diagnosis. Whole Slide Image (WSI) classification is often framed as a multiple instance learning (MIL) problem due to the high cost o...
Image Processing, Computer-Assisted Supervised Machine Learning Image Interpretation, Computer-Assisted Neoplasms Diagnosis, Computer-Assisted Machine Learning Algorithms Humans
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A deep architecture based on attention mechanisms for effective end-to-end detection of early and mature malaria parasites in a realistic scenario.

Computers in biology and medicine Jan 26, 2025
BACKGROUND: Malaria is a critical and potentially fatal disease caused by the Plasmodium parasite and is responsible for more than 600,000 deaths globally. Early and accurate detection of malaria parasites is crucial for effective treatment, yet conv...
Humans Diagnosis, Computer-Assisted Malaria Plasmodium Deep Learning Image Processing, Computer-Assisted
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A quantum-optimized approach for breast cancer detection using SqueezeNet-SVM.

Scientific reports Jan 25, 2025
Breast cancer is one of the most aggressive types of cancer, and its early diagnosis is crucial for reducing mortality rates and ensuring timely treatment. Computer-aided diagnosis systems provide automated mammography image processing, interpretatio...
Support Vector Machine Mammography Algorithms Databases, Factual Humans Female Breast Neoplasms Diagnosis, Computer-Assisted
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Two algorithms for improving model-based diagnosis using multiple observations and deep learning.

Neural networks : the official journal of the International Neural Network Society Jan 22, 2025
Model-based diagnosis (MBD) is a critical problem in artificial intelligence. Recent advancements have made it possible to address this challenge using methods like deep learning. However, current approaches that use deep learning for MBD often strug...
Artificial Intelligence Algorithms Deep Learning Diagnosis, Computer-Assisted Humans Neural Networks, Computer
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PEDRA-EFB0: colorectal cancer prognostication using deep learning with patch embeddings and dual residual attention.

Medical & biological engineering & computing Jan 21, 2025
In computer-aided diagnosis systems, precise feature extraction from CT scans of colorectal cancer using deep learning is essential for effective prognosis. However, existing convolutional neural networks struggle to capture long-range dependencies a...
Humans Deep Learning Neural Networks, Computer Prognosis Colorectal Neoplasms Tomography, X-Ray Computed Diagnosis, Computer-Assisted Algorithms
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Advanced Deep Learning Models for Melanoma Diagnosis in Computer-Aided Skin Cancer Detection.

Sensors (Basel, Switzerland) Jan 21, 2025
The most deadly type of skin cancer is melanoma. A visual examination does not provide an accurate diagnosis of melanoma during its early to middle stages. Therefore, an automated model could be developed that assists with early skin cancer detection...
Algorithms Deep Learning Dermoscopy Image Processing, Computer-Assisted Melanoma Diagnosis, Computer-Assisted Humans Skin Neoplasms Neural Networks, Computer
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Multiscale feature enhanced gating network for atrial fibrillation detection.

Computer methods and programs in biomedicine Jan 20, 2025
BACKGROUND AND OBJECTIVE: Atrial fibrillation (AF) is a significant cause of life-threatening heart disease due to its potential to lead to stroke and heart failure. Although deep learning-assisted diagnosis of AF based on ECG holds significance in c...
Diagnosis, Computer-Assisted Deep Learning Electrocardiography Neural Networks, Computer Algorithms Signal Processing, Computer-Assisted Atrial Fibrillation Humans
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Role of Artificial Intelligence in the Detection and Management of Premalignant and Malignant Lesions of the Esophagus and Stomach.

Gastrointestinal endoscopy clinics of North America Jan 18, 2025
The advent of artificial intelligence (AI) and deep learning algorithms, particularly convolutional neural networks, promises to address pitfalls, bridging the care for patients at high risk with improved detection (computer-aided detection [CADe]) a...
Deep Learning Stomach Neoplasms Humans Esophageal Neoplasms Diagnosis, Computer-Assisted Early Detection of Cancer Artificial Intelligence Precancerous Conditions Esophageal Squamous Cell Carcinoma
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Investigating the key principles in two-step heterogeneous transfer learning for early laryngeal cancer identification.

Scientific reports Jan 16, 2025
Data scarcity in medical images makes transfer learning a common approach in computer-aided diagnosis. Some disease classification tasks can rely on large homogeneous public datasets to train the transferred model, while others cannot, i.e., endoscop...
Humans Machine Learning Algorithms Image Interpretation, Computer-Assisted Laryngeal Neoplasms Diagnosis, Computer-Assisted Early Detection of Cancer
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Artificial intelligence in healthcare applications targeting cancer diagnosis-part II: interpreting the model outputs and spotlighting the performance metrics.

Oral surgery, oral medicine, oral pathology and oral radiology Jan 15, 2025
BACKGROUND: The lack of standardized performance assessment metrics and the inconsistent reporting of results can lead to the presentation of overly optimistic outcomes that fail to accurately represent key aspects of the Machine Learning framework a...
Humans Neural Networks, Computer Sensitivity and Specificity Neoplasms Diagnosis, Computer-Assisted Artificial Intelligence Machine Learning
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