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Histopathology based AI model predicts anti-angiogenic therapy response in renal cancer clinical trial.
Nature communications
Mar 17, 2025
Anti-angiogenic (AA) therapy is a cornerstone of metastatic clear cell renal cell carcinoma (ccRCC) treatment, but not everyone responds, and predictive biomarkers are lacking. CD31, a marker of vasculature, is insufficient, and the Angioscore, an RN...
Artificial intelligence for predicting interstitial fibrosis and tubular atrophy using diagnostic ultrasound imaging and biomarkers.
BMJ health & care informatics
Mar 17, 2025
BACKGROUND: Chronic kidney disease (CKD) is a global health concern characterised by irreversible renal damage that is often assessed using invasive renal biopsy. Accurate evaluation of interstitial fibrosis and tubular atrophy (IFTA) is crucial for ...
State-of-the-art for automated machine learning predicts outcomes in poor-grade aneurysmal subarachnoid hemorrhage using routinely measured laboratory & radiological parameters: coagulation parameters and liver function as key prognosticators.
Neurosurgical review
Mar 17, 2025
The objective of this study was to develop and evaluate automated machine learning (aML) models for predicting short-term (1-month) and medium-term (3-month) functional outcomes [Modified Rankin Scale (mRS)] in patients suffering from poor-grade aneu...
Prediction of prostate biopsy outcomes at different cut-offs of prostate-specific antigen using machine learning: a multicenter study.
Journal of the Egyptian National Cancer Institute
Mar 17, 2025
BACKGROUND: Machine learning (ML) is a significant area of artificial intelligence, which can improve the accuracy of predictive or diagnostic models for differentiating between prostate biopsy outcomes. This study aims to develop a novel decision-su...
Real time artificial intelligence assisted carotid artery stenting: a preliminary experience.
Journal of neurointerventional surgery
Mar 17, 2025
BACKGROUND: Neurointerventionalists must pay close attention to multiple devices on multiple screens simultaneously, which can lead to oversights and complications. Artificial intelligence (AI) has potential application in recognizing and monitoring ...
Obesity classification: a comparative study of machine learning models excluding weight and height data.
Revista da Associacao Medica Brasileira (1992)
Mar 17, 2025
OBJECTIVE: Obesity is a global health problem. The aim is to analyze the effectiveness of machine learning models in predicting obesity classes and to determine which model performs best in obesity classification.
Fully automatic categorical analysis of striatal subregions in dopamine transporter SPECT using a convolutional neural network.
Annals of nuclear medicine
Mar 16, 2025
OBJECTIVE: To provide fully automatic scanner-independent 5-level categorization of the [I]FP-CIT uptake in striatal subregions in dopamine transporter SPECT.
Automated classification of panoramic radiographs with inflammatory periapical lesions using a CNN-LSTM architecture.
Journal of dentistry
Mar 16, 2025
OBJECTIVES: Considering Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) network approaches have shown promising image classification performance, the aim of this study was to compare the performance of novel Convolutional Neural ...
Predictive modelling of knee osteoporosis.
BMC research notes
Mar 16, 2025
OBJECTIVE: The objective of this research was to develop a machine learning-based predictive model for osteoporosis screening using demographic and clinical data, including T-scores derived from calcaneus Quantitative Ultrasound (QUS). The study aime...
Freezing of gait detection: The effect of sensor type, position, activities, datasets, and machine learning model.
Journal of Parkinson's disease
Mar 16, 2025
BackgroundFreezing of gait (FoG) is a complex, frequent, and disabling motor symptom of Parkinson's disease (PD). Wearable technology has the potential to improve FoG assessment by providing objective, quantitative, and continuous monitoring.Objectiv...
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