AIMC Topic: Middle Aged

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Individual-Level Prediction of Exposure Therapy Outcome Using Structural and Functional MRI Data in Spider Phobia: A Machine-Learning Study.

Depression and anxiety
Machine-learning prediction studies have shown potential to inform treatment stratification, but recent efforts to predict psychotherapy outcomes with clinical routine data have only resulted in moderate prediction accuracies. Neuroimaging data showe...

Detecting Adverse Pathology of Prostate Cancer With a Deep Learning Approach Based on a 3D Swin-Transformer Model and Biparametric MRI: A Multicenter Retrospective Study.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Accurately detecting adverse pathology (AP) presence in prostate cancer patients is important for personalized clinical decision-making. Radiologists' assessment based on clinical characteristics showed poor performance for detecting AP p...

Automated prognosis of renal function decline in ADPKD patients using deep learning.

Zeitschrift fur medizinische Physik
An accurate prognosis of renal function decline in Autosomal Dominant Polycystic Kidney Disease (ADPKD) is crucial for early intervention. Current biomarkers used are height-adjusted total kidney volume (HtTKV), estimated glomerular filtration rate (...

Machine Learning Predicting Atrial Fibrillation as an Adverse Event in the Warfarin and Aspirin in Reduced Cardiac Ejection Fraction (WARCEF) Trial.

The American journal of medicine
BACKGROUND: Atrial fibrillation and heart failure commonly coexist due to shared pathophysiological mechanisms. Prompt identification of patients with heart failure at risk of developing atrial fibrillation would allow clinicians the opportunity to i...

Multiple switching between the biosimilar adalimumab PF-06410293 and reference adalimumab in patients with active rheumatoid arthritis: a phase 3, open-label, randomised, parallel-group study.

The Lancet. Rheumatology
BACKGROUND: An adalimumab biosimilar with an interchangeability designation could increase access to effective treatment for more patients. We aimed to assess the interchangeability of adalimumab biosimilar PF-06410293 (adalimumab-afzb) and reference...

3D Breast Cancer Segmentation in DCE-MRI Using Deep Learning With Weak Annotation.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Deep learning models require large-scale training to perform confidently, but obtaining annotated datasets in medical imaging is challenging. Weak annotation has emerged as a way to save time and effort.

Robot-assisted laparoscopic pyeloplasty is a valid option for ureteropelvic junction obstruction repair in adults with congenital renal abnormalities: a case series study.

BMC urology
BACKGROUND: Congenital renal anomalies are rare but may be associated with obstruction of the ureteropelvic junction. Given the rarity of simultaneous ureteropelvic junction obstruction [UPJO] and renal anomalies in the adult population, there is lim...

Detection of extracranial and intracranial calcified carotid artery atheromas in cone beam computed tomography using a deep learning convolutional neural network image segmentation approach.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVE: We leveraged an artificial intelligence deep-learning convolutional neural network (DL CNN) to detect calcified carotid artery atheromas (CCAAs) on cone beam computed tomography (CBCT) images.

A Novel Artificial Intelligence Model for Symmetry Evaluation in Breast Cancer Patients.

Aesthetic plastic surgery
INTRODUCTION: Artificial intelligence (AI) is a milestone for human technology. In medicine, AI is set to play an important role as we progress into a new era. In plastic surgery, AI can participate in breast symmetry assessment, which until now has ...