AIMC Topic: Diagnostic Imaging
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Self-supervised pre-training with contrastive and masked autoencoder methods for dealing with small datasets in deep learning for medical imaging.
Scientific reports
Nov 20, 2023
Deep learning in medical imaging has the potential to minimize the risk of diagnostic errors, reduce radiologist workload, and accelerate diagnosis. Training such deep learning models requires large and accurate datasets, with annotations for all tra...
Practical Applications of Artificial Intelligence in Spine Imaging: A Review.
Radiologic clinics of North America
Nov 18, 2023
Artificial intelligence (AI), a transformative technology with unprecedented potential in medical imaging, can be applied to various spinal pathologies. AI-based approaches may improve imaging efficiency, diagnostic accuracy, and interpretation, whic...
Understanding the factors influencing acceptability of AI in medical imaging domains among healthcare professionals: A scoping review.
Artificial intelligence in medicine
Nov 9, 2023
BACKGROUND: Artificial intelligence (AI) technology has the potential to transform medical practice within the medical imaging industry and materially improve productivity and patient outcomes. However, low acceptability of AI as a digital healthcare...
Accurate classification of major brain cell types using in vivo imaging and neural network processing.
PLoS biology
Nov 9, 2023
Comprehensive analysis of tissue cell type composition using microscopic techniques has primarily been confined to ex vivo approaches. Here, we introduce NuCLear (Nucleus-instructed tissue composition using deep learning), an approach combining in vi...
Molecular Graph-Based Deep Learning Algorithm Facilitates an Imaging-Based Strategy for Rapid Discovery of Small Molecules Modulating Biomolecular Condensates.
Journal of medicinal chemistry
Nov 8, 2023
Biomolecular condensates are proposed to cause diseases, such as cancer and neurodegeneration, by concentrating proteins at abnormal subcellular loci. Imaging-based compound screens have been used to identify small molecules that reverse or promote b...
A survey on cancer detection via convolutional neural networks: Current challenges and future directions.
Neural networks : the official journal of the International Neural Network Society
Nov 7, 2023
Cancer is a condition in which abnormal cells uncontrollably split and damage the body tissues. Hence, detecting cancer at an early stage is highly essential. Currently, medical images play an indispensable role in detecting various cancers; however,...
Best Practices for Artificial Intelligence and Machine Learning for Computer-Aided Diagnosis in Medical Imaging.
Journal of the American College of Radiology : JACR
Nov 2, 2023
["New Modalities in Cancer Imaging and Therapy" XVth edition of the workshop organized by the network "Tumor Targeting, Imaging, Radiotherapies" of the Cancéropôle Grand-Ouest, 5-8 October 2022, France].
Bulletin du cancer
Oct 23, 2023
The fifteenth edition of the international workshop organized by the "Tumour Targeting and Radiotherapies network" of the Cancéropôle Grand-Ouest focused on the latest advances in internal and external radiotherapy from different disciplinary angles:...
Enhancing radiomics and Deep Learning systems through the standardization of medical imaging workflows.
Scientific data
Oct 21, 2023
Recent advances in computer-aided diagnosis, treatment response and prognosis in radiomics and deep learning challenge radiology with requirements for world-wide methodological standards for labeling, preprocessing and image acquisition protocols. Th...
Assessing appropriate responses to ACR urologic imaging scenarios using ChatGPT and Bard.
Current problems in diagnostic radiology
Oct 20, 2023
Artificial intelligence (AI) has recently become a trending tool and topic regarding productivity especially with publicly available free services such as ChatGPT and Bard. In this report, we investigate if two widely available chatbots chatGPT and B...
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