Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 41,461 to 41,470 of 223,853 articles

[Basal ganglia and movement disorders : Part 1: the parkinsonian spectrum-Neuroradiological patterns and diagnostic considerations].

Radiologie (Heidelberg, Germany) Mar 16, 2026
Movement disorders are a frequent yet diagnostically unspecific reason for referral in routine neuroradiological practice. Hypokinetic syndromes with parkinsonism in particular regularly raise the question of an underlying neurodegenerative disorder,... read more 

Reply to the Letter to the Editor: A deep learning framework to stratify Nottingham histologic grade 2 breast tumors based on dynamic contrast-enhanced MRI.

European radiology Mar 16, 2026
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Predicting intrahepatic recurrence of colorectal cancer liver metastases after curative hepatectomy using a machine learning model with data integration of ultrasound radiomics and clinicopathological parameters.

Insights into imaging Mar 16, 2026
OBJECTIVES: To develop and validate a machine learning model integrating ultrasound radiomics and clinicopathological parameters to predict intrahepatic recurrence in colorectal cancer liver metastases (CRLM) patients after curative hepatectomy. MATE... read more 

Cerebrovascular CTA radiomics for objective collateral grading in acute ischemic stroke.

European radiology experimental Mar 16, 2026
OBJECTIVE: Collateral circulation is a key determinant of functional outcome after large vessel occlusion (LVO) and informs thrombectomy decisions. However, collateral grading is rater-dependent and error-prone. We developed an automated cerebrovascu... read more 

Deep learning-based identification of chronic pulmonary embolism on CTPA: a regional lung analysis using multiplanar MIP images.

European radiology experimental Mar 16, 2026
OBJECTIVE: Chronic pulmonary embolism (CPE) and chronic thromboembolic pulmonary hypertension (CTEPH) are challenging to diagnose, with delayed detection increasing mortality. We evaluated the performance of a convolutional neural network (CNN) in id... read more 

An integrated microfluidic system for automatic and self-validated analysis of cervical extracellular vesicle markers PD-L1 and ERBB3.

Analytical sciences : the international journal of the Japan Society for Analytical Chemistry Mar 16, 2026
The early and precise diagnosis of gynecological malignancies, such as cervical cancer, is critical for improving patient treatments. Extracellular vesicles (EVs), such as exosomes, which carry molecular signals from their parental cells, offer a pro... read more 

Advances in imaging modalities and tumor classification for vestibular schwannomas.

Journal of neuro-oncology Mar 16, 2026
PURPOSE: Vestibular schwannomas are benign tumors of the cerebellopontine angle that may causesignificant neurological morbidity. Magnetic resonance imaging (MRI) remainsthe diagnostic gold standard; however, recent advances in neuroradiologictechniq... read more 

Examining the gene network and prognostic biomarkers in the onset of colorectal cancer in stool samples using machine learning.

Discover oncology Mar 16, 2026
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Artificial Intelligence-enhanced Electrocardiography for Heart Failure Screening and Risk Stratification.

Current heart failure reports Mar 16, 2026
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Identified BIRC5 and HDAC1 as novel diagnostic biomarkers linked to centrosome-immune crosstalk for cutaneous squamous cell carcinoma via machine learning-based multi-omics analysis.

Discover oncology Mar 16, 2026
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