AI Medical Compendium Topic:
Diagnosis, Differential

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A methodological approach for deep learning to distinguish between meningiomas and gliomas on canine MR-images.

BMC veterinary research
BACKGROUND: Distinguishing between meningeal-based and intra-axial lesions by means of magnetic resonance (MR) imaging findings may occasionally be challenging. Meningiomas and gliomas account for most of the total primary brain neoplasms in dogs, an...

Detecting drug-resistant tuberculosis in chest radiographs.

International journal of computer assisted radiology and surgery
PURPOSE: Tuberculosis is a major global health threat claiming millions of lives each year. While the total number of tuberculosis cases has been decreasing over the last years, the rise of drug-resistant tuberculosis has reduced the chance of contro...

Second branchial cleft anomalies in children: a literature review.

Pediatric surgery international
Branchial cleft anomalies are the second most common head and neck congenital lesions in children. It may sometimes be a part of branchio-oto-renal (BOR) syndrome, so in patients with branchial cleft anomalies associated with a complaint of auricular...

Machine learning based on multi-parametric magnetic resonance imaging to differentiate glioblastoma multiforme from primary cerebral nervous system lymphoma.

European journal of radiology
PURPOSE: To evaluate the performance of a machine learning method based on texture features in multi-parametric magnetic resonance imaging (MRI) to differentiate a glioblastoma multiforme (GBM) from a primary cerebral nervous system lymphoma (PCNSL).

Complexity in mood disorder diagnosis: fMRI connectivity networks predicted medication-class of response in complex patients.

Acta psychiatrica Scandinavica
OBJECTIVE: This study determined the clinical utility of an fMRI classification algorithm predicting medication-class of response in patients with challenging mood diagnoses.

On differentiation between vasogenic edema and non-enhancing tumor in high-grade glioma patients using a support vector machine classifier based upon pre and post-surgery MRI images.

European journal of radiology
PURPOSE: High grade gliomas (HGGs) are infiltrative in nature. Differentiation between vasogenic edema and non-contrast enhancing tumor is difficult as both appear hyperintense in T-W/FLAIR images. Most studies involving differentiation between vasog...