AIMC Topic: Humans

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Evaluation of the humoral response induced by BBIBP-CorV vaccine by determining neutralizing antibodies in peruvian healthcare personnel.

Revista peruana de medicina experimental y salud publica
OBJECTIVE.: To determine the titer of antibodies against the receptor binding domain (RBD) of the spike protein (S) in health personnel between the 4th and 12th week after receiving the BBIBP-CorV vaccine (Sinopharm).

Artificial intelligence-based detection of atrial fibrillation from chest radiographs.

European radiology
OBJECTIVE: The purpose of this study was to develop an artificial intelligence (AI)-based model to detect features of atrial fibrillation (AF) on chest radiographs.

Value of deep learning reconstruction at ultra-low-dose CT for evaluation of urolithiasis.

European radiology
OBJECTIVES: To determine the diagnostic accuracy and image quality of ultra-low-dose computed tomography (ULDCT) with deep learning reconstruction (DLR) to evaluate patients with suspected urolithiasis, compared with ULDCT with hybrid iterative recon...

Quality of laparoscopic camera navigation in robot-assisted versus conventional laparoscopic surgery for rectal cancer: An analysis of surgical videos through a video processing computer software.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: To compare laparoscopic camera navigation (LCN) quality between robot-assisted laparoscopic surgery (RALS) and conventional laparoscopic surgery (CLS).

Multiple sclerosis cortical lesion detection with deep learning at ultra-high-field MRI.

NMR in biomedicine
Manually segmenting multiple sclerosis (MS) cortical lesions (CLs) is extremely time consuming, and past studies have shown only moderate inter-rater reliability. To accelerate this task, we developed a deep-learning-based framework (CLAIMS: Cortical...

Temporal shift and predictive performance of machine learning for heart transplant outcomes.

The Journal of heart and lung transplantation : the official publication of the International Society for Heart Transplantation
BACKGROUND: Outcome prediction following heart transplant is critical to explaining risks and benefits to patients and decision-making when considering potential organ offers. Given the large number of potential variables to be considered, this task ...

Deep learning derived automated ASPECTS on non-contrast CT scans of acute ischemic stroke patients.

Human brain mapping
Ischemic stroke is the most common type of stroke, ranked as the second leading cause of death worldwide. The Alberta Stroke Program Early CT Score (ASPECTS) is considered as a systematic method of assessing ischemic change on non-contrast CT scans (...

Deep learning for locally advanced nasopharyngeal carcinoma prognostication based on pre- and post-treatment MRI.

Computer methods and programs in biomedicine
PURPOSE: We aimed to predict the prognosis of advanced nasopharyngeal carcinoma (stage Ⅲ-Ⅳa) using Pre- and Post-treatment MR images based on deep learning (DL).

Transferability of multivariate extreme value models for safety assessment by applying artificial intelligence-based video analytics.

Accident; analysis and prevention
Traffic conflict techniques represent the state-of-the-art for road safety assessments. However, the lack of research on transferability of conflict-based crash risk models, which refers to applying the developed crash risk estimation models to a set...