AIMC Topic: Diagnosis, Differential
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Leveraging a Vision Transformer Model to Improve Diagnostic Accuracy of Cardiac Amyloidosis With Cardiac Magnetic Resonance.
JACC. Cardiovascular imaging
Dec 4, 2024
BACKGROUND: Cardiac magnetic resonance (CMR) imaging is an important diagnostic tool for diagnosis of cardiac amyloidosis (CA). However, discrimination of CA from other etiologies of myocardial disease can be challenging.
Male
Middle Aged
Deep Learning
Contrast Media
Female
Reproducibility of Results
Aged
Cardiomyopathy, Hypertrophic
Amyloidosis
Diagnosis, Differential
Cardiomyopathies
Predictive Value of Tests
Humans
Magnetic Resonance Imaging, Cine
Myocardium
Decision Support Techniques
Image Interpretation, Computer-Assisted
Retrospective Studies
RNA Editing Signatures Powered by Artificial Intelligence: A New Frontier in Differentiating Schizophrenia, Bipolar, and Schizoaffective Disorders.
International journal of molecular sciences
Dec 3, 2024
Mental health disorders are devastating illnesses, often misdiagnosed due to overlapping clinical symptoms. Among these conditions, bipolar disorder, schizophrenia, and schizoaffective disorder are particularly difficult to distinguish, as they share...
MRI classification and discrimination of spinal schwannoma and meningioma based on deep learning.
Journal of X-ray science and technology
Nov 27, 2024
BACKGROUD: Schwannoma (SCH) and meningiomas (MEN) are the two most common primary spinal cord tumors. Differentiating between them preoperatively remains a clinical challenge due to the substantial overlap in their clinical presentation and imaging c...
Differentiating atypical parkinsonian syndromes with hyperbolic few-shot contrastive learning.
NeuroImage
Nov 24, 2024
Differences in iron accumulation patterns have been observed in susceptibility-weighted images across different classes of atypical parkinsonian syndromes (APS). Deep learning methods have shown great potential in automatically detecting these differ...
Automatic discrimination between neuroendocrine carcinomas and grade 3 neuroendocrine tumors by deep learning of H&E images.
Computers in biology and medicine
Nov 21, 2024
Neuroendocrine neoplasms (NENs) arise from diffuse neuroendocrine cells and are categorized as either well-differentiated and less proliferative Neuroendocrine Tumors (NETs), divided into low (G1), middle (G2), and high grades (G3), or poorly differe...
Comparative Analysis of Diagnostic Performance: Differential Diagnosis Lists by LLaMA3 Versus LLaMA2 for Case Reports.
JMIR formative research
Nov 19, 2024
BACKGROUND: Generative artificial intelligence (AI), particularly in the form of large language models, has rapidly developed. The LLaMA series are popular and recently updated from LLaMA2 to LLaMA3. However, the impacts of the update on diagnostic p...
Model Based on Ultrasound Radiomics and Machine Learning to Preoperative Differentiation of Follicular Thyroid Neoplasm.
Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
Nov 18, 2024
OBJECTIVES: To evaluate the value of radiomics based on ultrasonography in differentiating follicular thyroid carcinoma (FTC) and follicular thyroid adenoma (FTA) and construct a tool for preoperative noninvasive predicting FTC and FTA.
Accuracy of Machine Learning in Discriminating Kawasaki Disease and Other Febrile Illnesses: Systematic Review and Meta-Analysis.
Journal of medical Internet research
Nov 18, 2024
BACKGROUND: Kawasaki disease (KD) is an acute pediatric vasculitis that can lead to coronary artery aneurysms and severe cardiovascular complications, often presenting with obvious fever in the early stages. In current clinical practice, distinguishi...
Image-based deep learning in diagnosing mycoplasma pneumonia on pediatric chest X-rays.
BMC pediatrics
Nov 11, 2024
BACKGROUND: Correctly diagnosing and accurately distinguishing mycoplasma pneumonia in children has consistently posed a challenge in clinical practice, as it can directly impact the prognosis of affected children. To address this issue, we analyzed ...
Artificial intelligence-assisted magnetic resonance imaging technology in the differential diagnosis and prognosis prediction of endometrial cancer.
Scientific reports
Nov 6, 2024
It aimed to analyze the value of deep learning algorithm combined with magnetic resonance imaging (MRI) in the risk diagnosis and prognosis of endometrial cancer (EC). Based on the deep learning convolutional neural network (CNN) architecture residua...
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