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...
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...
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...
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...
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...
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 ...
The future of multimodal artificial intelligence models for integrating imaging and clinical metadata: a narrative review.
Diagnostic and interventional radiology (Ankara, Turkey)
Oct 1, 2024
With the ongoing revolution of artificial intelligence (AI) in medicine, the impact of AI in radiology is more pronounced than ever. An increasing number of technical and clinical AI-focused studies are published each day. As these tools inevitably a...
Metabolic phenotyping combined with transcriptomics metadata fortifies the diagnosis of early-stage Hepatocellular carcinoma.
Journal of advanced research
Sep 6, 2024
INTRODUCTION: The low sensitivity of alpha-fetoprotein (AFP) renders it unsuitable as a stand-alone marker for early hepatocellular carcinoma (eHCC) surveillance. Therefore, additional blood-based biomarkers with enhanced sensitivities are required.
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 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...
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