Ai-based image analysis

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Image-based AI diagnostic performance for fatty liver: a systematic review and meta-analysis.

Not available

S-EPMC10712108 | biostudies-literature

AI-based histopathology image analysis reveals a distinct subset of endometrial cancers.

Not available

S-EPMC11208496 | biostudies-literature

Cost-effectiveness analysis of AI-based image quality control for perinatal ultrasound screening.

Not available

S-EPMC11654377 | biostudies-literature

Artificial intelligence-based identification of thin-cap fibroatheromas and clinical outcomes: the PECTUS-AI study.

Not available

S-EPMC12682388 | biostudies-literature

AI Deployment on GBM Diagnosis: A Novel Approach to Analyze Histopathological Images Using Image Feature-Based Analysis.

Not available

S-EPMC10605241 | biostudies-literature

Artificial intelligence-based histopathology image analysis identifies a novel subset of endometrial cancers with distinct genomic features and unfavourable outcome

PRJEB60600 | ENA

AI-Based RGB Image Generation From RG Fundus Images Using Pix2Pix: Validation by Quantitative and Observer-Based Evaluations.

Not available

S-EPMC12805957 | biostudies-literature

Automated AI-based image analysis for quantification and prediction of interstitial lung disease in systemic sclerosis patients.

Not available

S-EPMC11762107 | biostudies-literature

Deep visual multi-omics profiling reveals mechanisms that underly cancer cell differentiation and aggressiveness in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) exhibits significant intra-tumoral heterogeneity (ITH) at both morphological and genetic levels, complicating treatment and contributing to disease progression. Among these, rhabdoid ccRCCs stand out as highly aggressive tumors distinguished by cells with uniq...

ORGANISM(S): Homo sapiens (Human)

2025-02-21 | PXD061011 | Pride

AI-based lumbar central canal stenosis classification on sagittal MR images is comparable to experienced radiologists using axial images.

Not available

S-EPMC11913898 | biostudies-literature

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