AIMC Topic: Postoperative Period
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Machine learning-based prediction models affecting the recovery of postoperative bowel function for patients undergoing colorectal surgeries.
BMC surgery
May 10, 2024
PURPOSE: The debate surrounding factors influencing postoperative flatus and defecation in patients undergoing colorectal resection prompted this study. Our objective was to identify independent risk factors and develop prediction models for postoper...
Deep Learning for prediction of late recurrence of retinal detachment using preoperative and postoperative ultra-wide field imaging.
Acta ophthalmologica
Apr 29, 2024
PURPOSE: To elaborate a deep learning (DL) model for automatic prediction of late recurrence (LR) of rhegmatogenous retinal detachment (RRD) using pseudocolor and fundus autofluorescence (AF) ultra-wide field (UWF) images obtained preoperatively and ...
SAGL: A self-attention-based graph learning framework for predicting survival of colorectal cancer patients.
Computer methods and programs in biomedicine
Apr 2, 2024
BACKGROUND AND OBJECTIVE: Colorectal cancer (CRC) is one of the most commonly diagnosed cancers worldwide. The accurate survival prediction for CRC patients plays a significant role in the formulation of treatment strategies. Recently, machine learni...
A Longitudinal Analysis of Pre- and Post-Operative Dysmorphology in Metopic Craniosynostosis.
The Cleft palate-craniofacial journal : official publication of the American Cleft Palate-Craniofacial Association
Mar 14, 2024
OBJECTIVE: The purpose of this study is to objectively quantify the degree of overcorrection in our current practice and to evaluate longitudinal morphological changes using CranioRate, a novel machine learning skull morphology assessment tool.  Desi...
The weight of BMI in impacting postoperative and oncologic outcomes in pancreaticoduodenectomy is attenuated by a robotic approach.
Journal of robotic surgery
Feb 14, 2024
This study was undertaken to observe the effect of body mass index (BMI) on perioperative outcomes and survival when comparing robotic vs 'open' pancreaticoduodenectomy. With IRB approval, we prospectively followed 505 consecutive patients who underw...
Machine learning-based prediction of hip joint moment in healthy subjects, patients and post-operative subjects.
Computer methods in biomechanics and biomedical engineering
Feb 8, 2024
The application of machine learning in the field of motion capture research is growing rapidly. The purpose of the study is to implement a long-short term memory (LSTM) model able to predict sagittal plane hip joint moment (HJM) across three distinct...
Prediction of Postoperative Creatinine Levels by Artificial Intelligence after Partial Nephrectomy.
Medicina (Kaunas, Lithuania)
Jul 31, 2023
: Multiple factors are associated with postoperative functional outcomes, such as acute kidney injury (AKI), following partial nephrectomy (PN). The pre-, peri-, and postoperative factors are heavily intertwined and change dynamically, making it diff...
A spatio-temporal network for video semantic segmentation in surgical videos.
International journal of computer assisted radiology and surgery
Jun 22, 2023
PURPOSE: Semantic segmentation in surgical videos has applications in intra-operative guidance, post-operative analytics and surgical education. Models need to provide accurate predictions since temporally inconsistent identification of anatomy can h...
A Deep Learning Tool for Automated Landmark Annotation on Hip and Pelvis Radiographs.
The Journal of arthroplasty
May 24, 2023
BACKGROUND: Automatic methods for labeling and segmenting pelvis structures can improve the efficiency of clinical and research workflows and reduce the variability introduced with manual labeling. The purpose of this study was to develop a single de...
Prediction of postoperative cardiac events in multiple surgical cohorts using a multimodal and integrative decision support system.
Scientific reports
Jul 5, 2022
Postoperative patients are at risk of life-threatening complications such as hemodynamic decompensation or arrhythmia. Automated detection of patients with such risks via a real-time clinical decision support system may provide opportunities for earl...
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