AIMC Topic: Aged, 80 and over

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Establishment of a corneal ulcer prognostic model based on machine learning.

Scientific reports
Corneal infection is a major public health concern worldwide and the most common cause of unilateral corneal blindness. Toxic effects of different microorganisms, such as bacteria and fungi, worsen keratitis leading to corneal perforation even with o...

A cutting-edge deep learning-and-radiomics-based ultrasound nomogram for precise prediction of axillary lymph node metastasis in breast cancer patients ≥ 75 years.

Frontiers in endocrinology
OBJECTIVE: The objective of this study was to develop a deep learning-and-radiomics-based ultrasound nomogram for the evaluation of axillary lymph node (ALN) metastasis risk in breast cancer patients ≥ 75 years.

Predicting Secondary Vertebral Compression Fracture After Vertebral Augmentation via CT-Based Machine Learning Radiomics-Clinical Model.

Academic radiology
RATIONALE AND OBJECTIVES: Secondary vertebral compression fractures (SVCF) are very common in patients after vertebral augmentation (VA). The aim of this study was to establish a radiomic-based model to predict SVCF and specify appropriate treatment ...

Habitat radiomics and deep learning fusion nomogram to predict EGFR mutation status in stage I non-small cell lung cancer: a multicenter study.

Scientific reports
Develop a radiomics nomogram that integrates deep learning, radiomics, and clinical variables to predict epidermal growth factor receptor (EGFR) mutation status in patients with stage I non-small cell lung cancer (NSCLC). We retrospectively included ...

Evaluation of fragility fracture risk using deep learning based on ultrasound radio frequency signal.

Endocrine
BACKGROUND: It was essential to identify individuals at high risk of fragility fracture and prevented them due to the significant morbidity, mortality, and economic burden associated with fragility fracture. The quantitative ultrasound (QUS) showed p...

Low energy virtual monochromatic CT with deep learning image reconstruction to improve delineation of endoleaks.

Clinical radiology
AIM: This study aimed to investigate the utility of low-energy virtual monochromatic imaging (VMI) combined with deep-learning image reconstruction (DLIR) in improving the delineation of endoleaks (ELs) after endovascular aortic repair (EVAR) in cont...

A model for identifying potentially inappropriate medication used in older people with dementia: a machine learning study.

International journal of clinical pharmacy
BACKGROUND: Older adults with dementia often face the risk of potentially inappropriate medication (PIM) use. The quality of PIM evaluation is hindered by researchers' unfamiliarity with evaluation criteria for inappropriate drug use. While tradition...

Simplifying risk stratification for thyroid nodules on ultrasound: validation and performance of an artificial intelligence thyroid imaging reporting and data system.

Current problems in diagnostic radiology
PURPOSE: To validate the performance of a recently created risk stratification system (RSS) for thyroid nodules on ultrasound, the Artificial Intelligence Thyroid Imaging Reporting and Data System (AI TI-RADS).

Prognostic prediction model for salivary gland carcinoma based on machine learning.

International journal of oral and maxillofacial surgery
Although rare overall, salivary gland carcinomas (SGCs) are among the most common oral and maxillofacial malignancies. The aim of this study was to develop a machine learning-based model to predict the survival of patients with SGC. Patients in whom ...