AIMC Topic: Nomograms
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Multimodal nomogram integrating deep learning radiomics and hemodynamic parameters for early prediction of post-craniotomy intracranial hypertension.
Scientific reports
Jul 2, 2025
To evaluate the effectiveness of deep learning radiomics nomogram in distinguishing early intracranial hypertension (IH) following primary decompressive craniectomy (DC) in patients with severe traumatic brain injury (TBI) and to demonstrate its pote...
AI-based CT assessment of 3117 vertebrae reveals significant sex-specific vertebral height differences.
Scientific reports
Jul 1, 2025
Predicting vertebral height is complex due to individual factors. AI-based medical imaging analysis offers new opportunities for vertebral assessment. Thereby, these novel methods may contribute to sex-adapted nomograms and vertebral height predictio...
Unveiling the mechanisms and promising molecular targets of curcumin in pancreatic cancer through multi-dimensional data.
Scientific reports
Jul 1, 2025
Pancreatic cancer (PC) is a highly aggressive and fatal malignancy, primarily affecting older males. Curcumin, a potential anti-cancer agent, has been shown to regulate key molecules in cancer progression, but its specific mechanisms in PC remain unc...
Harnessing the machine learning and nomogram models: elevating prognostication in nonmetastatic gastric cancer with "double invasion" for personalized patient care.
European journal of medical research
Jun 23, 2025
OBJECTIVE: To develop and validate a machine learning framework combined with a nomogram for predicting recurrence after radical gastrectomy in patients with vascular and neural invasion.
Extremity Soft Tissue Sarcoma Reconstruction Nomograms: A Clinicoradiomic, Machine Learning-Powered Predictor of Postoperative Outcomes.
JCO clinical cancer informatics
Jun 11, 2025
PURPOSE: The choice of wound closure modality after limb-sparing extremity soft-tissue sarcoma (eSTS) resection is fraught with uncertainty. Leveraging machine learning and clinicoradiomic data, we developed Sarcoma Reconstruction Nomograms (SARCON),...
The value of intratumoral and peritumoral ultrasound radiomics model constructed using multiple machine learning algorithms for non-mass breast cancer.
Scientific reports
Jun 6, 2025
To investigate the diagnostic capability of multiple machine learning algorithms combined with intratumoral and peritumoral ultrasound radiomics models for non-massive breast cancer in dense breast backgrounds. Manual segmentation of ultrasound image...
Development and validation of a predictive nomogram for bilateral posterior condylar displacement using cone-beam computed tomography and machine-learning algorithms: a retrospective observational study.
BMC oral health
Jun 5, 2025
BACKGROUND: Temporomandibular disorders (TMDs) are frequently associated with posterior condylar displacement; however, early prediction of this displacement remains a significant challenge. Therefore, in this study, we aimed to develop and evaluate ...
Screening of glioma susceptibility SNPs and construction of risk models based on machine learning algorithms.
BMC neurology
Jun 5, 2025
BACKGROUND: Glioma is a common primary malignant brain tumor. This study aimed to develop a predictive model for glioma risk by these screened key SNPs in the Chinese Han population.
Construction and validation of a prognostic nomogram model integrating machine learning-pathomics and clinical features in IDH-wildtype glioblastoma.
Journal of translational medicine
Jun 3, 2025
BACKGROUND: Novel diagnostic criteria for glioblastoma (GBM) in the 2021 WHO classification emphasize the importance of integrating pathological and molecular features. Pathomics, which involves the extraction of digital pathology data, is gaining si...
Development of a machine learning-based predictive nomogram for screening children with juvenile idiopathic arthritis: a pseudo-longitudinal study of 223,195 children in the United States.
Frontiers in public health
May 29, 2025
BACKGROUND: Juvenile idiopathic arthritis (JIA) is a prevalent chronic rheumatological condition in children, with reported prevalence ranging from 12. 8 to 45 per 100,000 and incidence rates from 7.8 to 8.3 per 100,000 person-years. The diagnosis of...
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