AIMC Topic: Benchmarking
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Deep learning-based 3D brain multimodal medical image registration.
Medical & biological engineering & computing
Nov 8, 2023
Medical image registration is a critical preprocessing step in medical image analysis. While traditional medical image registration techniques have matured, their registration speed and accuracy still fall short of clinical requirements. In this pape...
Deep Generative Models in Drug Molecule Generation.
Journal of chemical information and modeling
Nov 7, 2023
The discovery of new drugs has important implications for human health. Traditional methods for drug discovery rely on experiments to optimize the structure of lead molecules, which are time-consuming and high-cost. Recently, artificial intelligence ...
Algorithmic Fairness of Machine Learning Models for Alzheimer Disease Progression.
JAMA network open
Nov 1, 2023
IMPORTANCE: Predictive models using machine learning techniques have potential to improve early detection and management of Alzheimer disease (AD). However, these models potentially have biases and may perpetuate or exacerbate existing disparities.
FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation.
IEEE transactions on neural networks and learning systems
Oct 27, 2023
The increase of available large clinical and experimental datasets has contributed to a substantial amount of important contributions in the area of biomedical image analysis. Image segmentation, which is crucial for any quantitative analysis, has es...
Technical/Algorithm, Stakeholder, and Society (TASS) barriers to the application of artificial intelligence in medicine: A systematic review.
Journal of biomedical informatics
Oct 25, 2023
INTRODUCTION: The use of artificial intelligence (AI), particularly machine learning and predictive analytics, has shown great promise in health care. Despite its strong potential, there has been limited use in health care settings. In this systemati...
DeepXplainer: An interpretable deep learning based approach for lung cancer detection using explainable artificial intelligence.
Computer methods and programs in biomedicine
Oct 24, 2023
BACKGROUND AND OBJECTIVE: Artificial intelligence (AI) has several uses in the healthcare industry, some of which include healthcare management, medical forecasting, practical making of decisions, and diagnosis. AI technologies have reached human-lik...
Democratizing Artificial Intelligence Imaging Analysis With Automated Machine Learning: Tutorial.
Journal of medical Internet research
Oct 12, 2023
Deep learning-based clinical imaging analysis underlies diagnostic artificial intelligence (AI) models, which can match or even exceed the performance of clinical experts, having the potential to revolutionize clinical practice. A wide variety of aut...
MLNet: Metaheuristics-Based Lightweight Deep Learning Network for Cervical Cancer Diagnosis.
IEEE journal of biomedical and health informatics
Oct 5, 2023
One of the leading causes of cancer-related deaths among women is cervical cancer. Early diagnosis and treatment can minimize the complications of this cancer. Recently, researchers have designed and implemented many deep learning-based automated cer...
Detecting changes in the performance of a clinical machine learning tool over time.
EBioMedicine
Oct 2, 2023
BACKGROUND: Excessive use of blood cultures (BCs) in Emergency Departments (EDs) results in low yields and high contamination rates, associated with increased antibiotic use and unnecessary diagnostics. Our team previously developed and validated a m...
Towards Building a Trustworthy Deep Learning Framework for Medical Image Analysis.
Sensors (Basel, Switzerland)
Sep 27, 2023
Computer vision and deep learning have the potential to improve medical artificial intelligence (AI) by assisting in diagnosis, prediction, and prognosis. However, the application of deep learning to medical image analysis is challenging due to limit...
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