AIMC Topic: Machine Learning
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Ensemble machine learning prediction model for clinical refraction using partial interferometry measurements in childhood.
PloS one
Jul 10, 2025
PURPOSE: To develop an ensemble machine learning prediction model for clinical refraction in childhood using partial interferometry measurements.
Predicting the sonication energy for focused ultrasound surgery treatment of breast fibroadenomas using machine learning algorithms.
International journal of hyperthermia : the official journal of European Society for Hyperthermic Oncology, North American Hyperthermia Group
Jul 9, 2025
PURPOSE: To establish a predictive model for the sonication energy required for focused ultrasound surgery (FUS) of breast fibroadenomas.
A novel machine-learning algorithm to screen for trisomy 21 in first-trimester singleton pregnancies.
Journal of obstetrics and gynaecology : the journal of the Institute of Obstetrics and Gynaecology
Jul 9, 2025
BACKGROUND: Antenatal screening for Trisomy 21 (T21) in the UK is performed primarily in the first trimester. Nuchal Translucency (NT), gestational age, Free β-HCG and PAPP-A are used in combination, creating the 'combined' test. Multivariate Gaussia...
Machine learning-based prediction model for post-ERCP cholangitis in patients with malignant biliary obstruction: a retrospective multicenter study.
Surgical endoscopy
Jul 9, 2025
BACKGROUND: Endoscopic retrograde cholangiopancreatography (ERCP) is the preferred palliative treatment for patients with unresectable malignant biliary obstruction (MBO), which can relieve biliary obstruction and prolong survival. Post-ERCP cholangi...
Predicting the prognosis of radical gastrectomy for patients with locally advanced gastric cancer after neoadjuvant chemotherapy using machine learning technology: a multicenter study in China.
Surgical endoscopy
Jul 9, 2025
BACKGROUND: Neoadjuvant chemotherapy (NAC) can improve the prognosis of patients with locally advanced gastric cancer (LAGC). However, precise models for accurate prognostic predictions are lacking. We aimed to utilize Cox regression and integrate va...
Development of an explainable machine learning model for predicting device-related pressure injuries in clinical settings.
BMC medical informatics and decision making
Jul 9, 2025
BACKGROUND: Device-related pressure injury (DRPI) is a prevalent and severe problem for patients using medical devices. Timely identification of patients at high risk of DRPI is crucial for healthcare providers to make informed decisions and prevent ...
Construction and evaluation of a height prediction model for children with growth disorders treated with recombinant human growth hormone.
BMC endocrine disorders
Jul 9, 2025
BACKGROUND: Height gain in children with growth disorders undergoing recombinant human growth hormone (rhGH) therapy shows considerable variability. Predicting treatment outcomes is essential for optimizing individualized treatment strategies.
A machine learning model reveals invisible microscopic variation in acute ischaemic stroke (≤ 6 h) with non-contrast computed tomography.
BMC medical imaging
Jul 9, 2025
BACKGROUND: In most medical centers, particularly in primary hospitals, non-contrast computed tomography (NCCT) serves as the primary imaging modality for diagnosing acute ischemic stroke. However, due to the small density difference between the infa...
An interpretable dynamic ensemble selection multiclass imbalance approach with ensemble imbalance learning for predicting road crash injury severity.
Scientific reports
Jul 9, 2025
Accurate prediction of crash injury severity and understanding the seriousness of multi-classification injuries is vital for informing authorities and the public. This Knowledge is crucial for enhancing road safety and reducing congestion, as differe...
Enhancing automated detection and classification of dementia in individuals with cognitive impairment using artificial intelligence techniques.
Scientific reports
Jul 9, 2025
Dementia is a degenerative and chronic disorder, increasingly prevalent among older adults, posing significant challenges in providing appropriate care. As the number of dementia cases continues to rise, delivering optimal care becomes more complex. ...
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