Artificial Intelligence Medical Compendium

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

Showing 1 to 10 of 199,772 articles

Neural Response to Familiar Names Predicts Outcome of Comatose ICU Patients: A Prospective Observational Cohort Study.

Nature communications Jun 4, 2026
Predicting the outcome of comatose patients in the intensive care unit (ICU) can inform decision making but remains challenging. Recent studies suggest that task-state electroencephalography (EEG) can detect covert cognition and facilitate patient pr... read more 

How good are 'AI doctors' - and will they take over medicine?

Nature Jun 3, 2026
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Advances in the diagnosis and detection of chronic kidney disease.

Lancet (London, England) Jun 3, 2026
Chronic kidney disease affects 788-844 million adults worldwide and is projected to become the fifth leading cause of death by 2040. Global burden estimates remain limited by ascertainment bias and inadequate access to testing, particularly in low-in... read more 

Validation of a deep-learning based thrombus classifier on digital subtraction angiography using a large-scale dataset.

Neuroradiology Jun 4, 2026
PURPOSE: Digital subtraction angiography (DSA) interpretation is observer dependent. This study evaluated the diagnostic performance of an existing deep-learning (DL) based thrombus classifier prior to clinical application. The intended use of the mo... read more 

Shortening MRI scanning time for acute ischemic stroke: analysis of the effect of 3.0T MRI compressed sensing deep learning reconstruction.

Emergency radiology Jun 4, 2026
BACKGROUND: Acute ischemic stroke requires rapid and accurate MRI diagnosis. This study aimed to evaluate whether 3.0T brain MRI with compressed sensing deep learning reconstruction (CS‑DLR) can reduce scanning time while maintaining diagnostic image... read more 

Clinical indicators associated with pericardial effusion in rheumatoid arthritis: a machine learning-based analysis.

Clinical rheumatology Jun 4, 2026
BACKGROUND: Pericardial effusion (PE) is a frequent yet underdiagnosed complication of rheumatoid arthritis (RA), with substantial mortality risk. Nevertheless, early detection remains challenging due to nonspecific presentations and the limited feas... read more 

Machine learning-based integration and comparison of ADC map radiomics with conventional imaging markers for cholesteatoma diagnosis.

Neuroradiology Jun 4, 2026
PURPOSE: To compare the diagnostic performance of apparent diffusion coefficient (ADC) map-based radiomics with conventional CT and DWI for differentiating cholesteatoma from non-cholesteatomatous middle ear lesions and to evaluate the incremental va... read more 

CT-based deep learning radiogenomics for predicting key glioma genotypes (IDH, ATRX, EGFR, TP53).

Neuroradiology Jun 4, 2026
PURPOSE: Molecular subtyping guides diagnosis and targeted therapy for gliomas. Although MRI-the current imaging standard-can be time-consuming and is sometimes contraindicated, computed tomography (CT) is faster, more widely available, and often pre... read more 

A comparative analysis of deep learning models for disease classification in multi-organ histopathological images.

Scientific reports Jun 4, 2026
Histopathological whole slide images (WSIs) provide critical information for disease diagnosis, yet their interpretation remains a time-consuming and expertise-dependent process. Recent advances in deep learning have shown promise in automating and i... read more 

Federated MobileNetV2 with ensemble meta-learning for privacy-preserving brain tumor classification.

Scientific reports Jun 4, 2026
The identification of brain tumors from MRI images is very crucial for the selection of an appropriate treatment. However, the existing solution has issues with privacy and data sharing. To address this challenge, this paper proposes the use of feder... read more 
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