AIMC Topic: Female

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Deep learning-based body composition analysis from whole-body magnetic resonance imaging to predict all-cause mortality in a large western population.

EBioMedicine
BACKGROUND: Manually extracted imaging-based body composition measures from a single-slice area (A) have shown associations with clinical outcomes in patients with cardiometabolic disease and cancer. With advances in artificial intelligence, fully au...

A Machine Learning-Based Prediction Model for the Probability of Fall Risk Among Chinese Community-Dwelling Older Adults.

Computers, informatics, nursing : CIN
Fall is a common adverse event among older adults. This study aimed to identify essential fall factors and develop a machine learning-based prediction model to predict the fall risk category among community-dwelling older adults, leading to earlier i...

Machine learning to predict lymph node metastasis in T1 esophageal squamous cell carcinoma: a multicenter study.

International journal of surgery (London, England)
BACKGROUND: Existing models do poorly when it comes to quantifying the risk of lymph node metastases (LNM). This study aimed to develop a machine-learning model for LNM in patients with T1 esophageal squamous cell carcinoma (ESCC).

Impact of an AI-based laparoscopic cholecystectomy coaching program on the surgical performance: a randomized controlled trial.

International journal of surgery (London, England)
BACKGROUND: Laparoscopic cholecystectomy (LC) is the gold standard for treating symptomatic gallstones but carries inherent risks like bile duct injury. While the critical view of safety (CVS) is advocated to mitigate bile duct injury, its real-world...

Development and validation of a deep learning model for predicting gastric cancer recurrence based on CT imaging: a multicenter study.

International journal of surgery (London, England)
INTRODUCTION: The postoperative recurrence of gastric cancer (GC) has a significant impact on the overall prognosis of patients. Therefore, accurately predicting the postoperative recurrence of GC is crucial.

Predicting Short-Term Mortality in Patients With Acute Pulmonary Embolism With Deep Learning.

Circulation journal : official journal of the Japanese Circulation Society
BACKGROUND: Accurate prediction of short-term mortality in patients with acute pulmonary embolism (PE) is critical for optimizing treatment strategies and improving patient outcomes. The Pulmonary Embolism Severity Index (PESI) is the current referen...

Using machine learning models for predicting monthly iPTH levels in hemodialysis patients.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Intact parathyroid hormone (iPTH), also known as active parathyroid hormone, is an important indicator commonly for monitoring secondary hyperparathyroidism (SHPT) in patients undergoing hemodialysis. The aim of this study w...

Estimating Ground Reaction Forces from Gait Kinematics in Cerebral Palsy: A Convolutional Neural Network Approach.

Annals of biomedical engineering
PURPOSE: While gait analysis is essential for assessing neuromotor disorders like cerebral palsy (CP), capturing accurate ground reaction force (GRF) measurements during natural walking presents challenges, particularly due to variations in gait patt...

Psychosocial effects of a humanoid robot on informal caregivers of people with dementia: A randomised controlled trial with nested interviews.

International journal of nursing studies
BACKGROUND: Dementia rates are rising globally, impacting healthcare systems and society. The care of people with dementia is largely provided by informal caregivers (e.g., family, friends), which can present significant challenges and increase careg...