AIMC Topic: Metadata

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Proposal for Using AI to Assess Clinical Data Integrity and Generate Metadata: Algorithm Development and Validation.

JMIR medical informatics Jun 30, 2025
BACKGROUND: Evidence-based medicine combines scientific research, clinical expertise, and patient preferences to enhance the patient outcomes and improve health care quality. Clinical data are crucial in aligning medical decisions with evidence-based...
Humans Reproducibility of Results Data Accuracy Metadata Artificial Intelligence Machine Learning Algorithms
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Gaussian random fields as an abstract representation of patient metadata for multimodal medical image segmentation.

Scientific reports May 29, 2025
Growing rates of chronic wound occurrence, especially in patients with diabetes, has become a recent concerning trend. Chronic wounds are difficult and costly to treat, and have become a serious burden on health care systems worldwide. Innovative dee...
Metadata Humans Normal Distribution Algorithms Image Processing, Computer-Assisted Deep Learning Diabetic Foot
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Instant prediction of scientific paper cited potential based on semantic and metadata features: Taking artificial intelligence field as an example.

PloS one Dec 2, 2024
With the continuous increase in the number of academic researchers, the volume of scientific papers is also increasing rapidly. The challenge of identifying papers with greater potential academic impact from this large pool has received increasing at...
Metadata Machine Learning Humans Semantics Bibliometrics Artificial Intelligence Publications
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Automated mapping of electronic data capture fields to SDTM.

PloS one Nov 7, 2024
OBJECTIVE: The goal of this work is to reduce the amount of manual work required to go from data capture to regulatory submission. It will be shown that the use of Siamese networks will allow for the generation of embeddings that can be used by tradi...
Algorithms Metadata Humans Neural Networks, Computer Machine Learning
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A cross-attention-based deep learning approach for predicting functional stroke outcomes using 4D CTP imaging and clinical metadata.

Medical image analysis Oct 30, 2024
Acute ischemic stroke (AIS) remains a global health challenge, leading to long-term functional disabilities without timely intervention. Spatio-temporal (4D) Computed Tomography Perfusion (CTP) imaging is crucial for diagnosing and treating AIS due t...
Female Aged Male Humans Stroke Metadata Thrombectomy Middle Aged Deep Learning Ischemic Stroke Perfusion Imaging Four-Dimensional Computed Tomography
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Data flow in clinical laboratories: could metadata and peridata bridge the gap to new AI-based applications?

Clinical chemistry and laboratory medicine Oct 7, 2024
In the last decades, clinical laboratories have significantly advanced their technological capabilities, through the use of interconnected systems and advanced software. Laboratory Information Systems (LIS), introduced in the 1970s, have transformed ...
Clinical Laboratory Information Systems Metadata Humans Laboratories, Clinical Artificial Intelligence Software
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Leveraging AI and patient metadata to develop a novel risk score for skin cancer detection.

Scientific reports Sep 6, 2024
Melanoma of the skin is the 17th most common cancer worldwide. Early detection of suspicious skin lesions (melanoma) can increase 5-year survival rates by 20%. The 7-point checklist (7PCL) has been extensively used to suggest urgent referrals for pat...
Metadata Adult Male Middle Aged Risk Assessment Early Detection of Cancer Skin Neoplasms Risk Factors Aged Female Melanoma Humans Artificial Intelligence Machine Learning
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Metadata information and fundus image fusion neural network for hyperuricemia classification in diabetes.

Computer methods and programs in biomedicine Aug 23, 2024
OBJECTIVE: In diabetes mellitus patients, hyperuricemia may lead to the development of diabetic complications, including macrovascular and microvascular dysfunction. However, the level of blood uric acid in diabetic patients is obtained by sampling p...
Image Processing, Computer-Assisted Glomerular Filtration Rate Diabetes Mellitus Fundus Oculi Hyperuricemia Neural Networks, Computer Male Uric Acid Algorithms Metadata Middle Aged Aged Female Deep Learning Adult Humans
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Metadata-enhanced contrastive learning from retinal optical coherence tomography images.

Medical image analysis Aug 10, 2024
Deep learning has potential to automate screening, monitoring and grading of disease in medical images. Pretraining with contrastive learning enables models to extract robust and generalisable features from natural image datasets, facilitating label-...
Macular Degeneration Image Interpretation, Computer-Assisted Metadata Deep Learning Humans Tomography, Optical Coherence Retina
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Patient Re-Identification Based on Deep Metric Learning in Trunk Computed Tomography Images Acquired from Devices from Different Vendors.

Journal of imaging informatics in medicine Feb 16, 2024
During radiologic interpretation, radiologists read patient identifiers from the metadata of medical images to recognize the patient being examined. However, it is challenging for radiologists to identify "incorrect" metadata and patient identificati...
Humans Tomography, X-Ray Computed Deep Learning Metadata Torso
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