AIMC Topic: Postoperative Period

Clear Filters Showing 101 to 110 of 131 articles

[Application Practice of AI Empowering Post-discharge Specialized Disease Management in Postoperative Rehabilitation of the Lung Cancer Patients Undergoing Surgery].

Zhongguo fei ai za zhi = Chinese journal of lung cancer
BACKGROUND: Lung cancer is the leading malignancy in China in terms of both incidence and mortality. With increased health awareness and the widespread use of low-dose computed tomography (CT), early diagnosis rates have been steadily improving. Surg...

A machine learning approach to predicting postoperative recurrence in pediatric chronic rhinosinusitis: identification of key metabolic biomarkers.

American journal of otolaryngology
BACKGROUND: Pediatric chronic rhinosinusitis (CRS) is a common chronic inflammatory disease with a high recurrence rate after surgery. This study aimed to construct and validate a machine learning-based predictive model to predict the risk of postope...

[Application of Photoplethysmography Combined with Deep Learning in Postoperative Monitoring of Flaps].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
OBJECTIVE: Photoelectric volumetric tracing (PPG) exhibits high sensitivity and specificity in flap monitoring. Deep learning (DL) is capable of automatically and robustly extracting features from raw data. In this study, we propose combining PPG wit...

[Research progress and prospects of artificial intelligence in diagnosis and treatment of colorectal cancer].

Zhonghua wei chang wai ke za zhi = Chinese journal of gastrointestinal surgery
Colorectal cancer is one of the most common malignant tumors worldwide. Due to the heterogeneity in patient outcomes and treatment responses to standard therapy regimens, personalized diagnostic and therapeutic strategies have remained a focus of sus...

[Deep Learning-Based Identification of Common Complication Features of Surgical Incisions].

Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
OBJECTIVE: In recent years, due to the development of accelerated recovery after surgery and day surgery in the field of surgery, the average length-of-stay of patients has been shortened and patients stay at home for post-surgical recovery and heali...

[Deep Learning-based Risk Prediction Model for Postoperative Healthcare-associated Infections].

Zhongguo yi xue ke xue yuan xue bao. Acta Academiae Medicinae Sinicae
Objective To develop a risk prediction model combining pre/intraoperative risk factors and intraoperative vital signs for postoperative healthcare-associated infection(HAI)based on deep learning. Methods We carried out a retrospective study based on ...

International Validation of the SORG Machine-learning Algorithm for Predicting the Survival of Patients with Extremity Metastases Undergoing Surgical Treatment.

Clinical orthopaedics and related research
BACKGROUND: The Skeletal Oncology Research Group machine-learning algorithms (SORG-MLAs) estimate 90-day and 1-year survival in patients with long-bone metastases undergoing surgical treatment and have demonstrated good discriminatory ability on inte...

Predicting the Aortic Aneurysm Postoperative Risks Based on Russian Integrated Data.

Studies in health technology and informatics
This article describes the results of feature extraction from unstructured medical records and prediction of postoperative complications for patients with thoracic aortic aneurysm operations using machine learning algorithms. The datasets from two di...