AIMC Topic: Retrospective Studies

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Deep-learning reconstructed lumbar spine 3D MRI for surgical planning: pedicle screw placement and geometric measurements compared to CT.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
PURPOSE: To test equivalency of deep-learning 3D lumbar spine MRI with "CT-like" contrast to CT for virtual pedicle screw planning and geometric measurements in robotic-navigated spinal surgery.

Predicting overall survival and prophylactic cranial irradiation benefit in small-cell lung cancer with CT-based deep learning: A retrospective multicenter study.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: To develop a computed tomography (CT)-based deep learning model to predict overall survival (OS) among small-cell lung cancer (SCLC) patients and identify patients who could benefit from prophylactic cranial irradiation (PCI) ...

Detection of urinary tract stones on submillisievert abdominopelvic CT imaging with deep-learning image reconstruction algorithm (DLIR).

Abdominal radiology (New York)
PURPOSE: Urolithiasis is a chronic condition that leads to repeated CT scans throughout the patient's life. The goal was to assess the diagnostic performance and image quality of submillisievert abdominopelvic computed tomography (CT) using deep lear...

Automatic segmentation of hepatocellular carcinoma on dynamic contrast-enhanced MRI based on deep learning.

Physics in medicine and biology
. Precise hepatocellular carcinoma (HCC) detection is crucial for clinical management. While studies focus on computed tomography-based automatic algorithms, there is a rareness of research on automatic detection based on dynamic contrast enhanced (D...

Artificial intelligence-based quantitative coronary angiography of major vessels using deep-learning.

International journal of cardiology
BACKGROUND: Quantitative coronary angiography (QCA) offers objective and reproducible measures of coronary lesions. However, significant inter- and intra-observer variability and time-consuming processes hinder the practical application of on-site QC...

Predicting long-term progression of Alzheimer's disease using a multimodal deep learning model incorporating interaction effects.

Journal of translational medicine
BACKGROUND: Identifying individuals with mild cognitive impairment (MCI) at risk of progressing to Alzheimer's disease (AD) provides a unique opportunity for early interventions. Therefore, accurate and long-term prediction of the conversion from MCI...

Development and validation of 'Patient Optimizer' (POP) algorithms for predicting surgical risk with machine learning.

BMC medical informatics and decision making
BACKGROUND: Pre-operative risk assessment can help clinicians prepare patients for surgery, reducing the risk of perioperative complications, length of hospital stay, readmission and mortality. Further, it can facilitate collaborative decision-making...

Learning curves for itinerant nurses to master the operation skill of Ti-robot-assisted spinal surgery equipment by CUSUM analysis: A pilot study.

PloS one
This study aimed to investigate the minimum number of operations required for itinerant nurses in the operating room to master the skills needed to operate the Ti-robot-assisted spinal surgery equipment. Additionally, we aimed to provide a correspond...