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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...

Assessing the Efficacy and Clinical Utility of Artificial Intelligence Scribes in Urology.

Urology
OBJECTIVE: To assess the quality of artificial intelligence (AI) scribes and to evaluate their impact on urologic practice.

A novel AI-based score for assessing the prognostic value of intra-epithelial lymphocytes in oral epithelial dysplasia.

British journal of cancer
BACKGROUND: Oral epithelial dysplasia (OED) poses a significant clinical challenge due to its potential for malignant transformation and the lack of reliable prognostic markers. Current OED grading systems do not reliably predict transformation and s...

Identification of an immune-related gene panel for the diagnosis of pulmonary arterial hypertension using bioinformatics and machine learning.

International immunopharmacology
OBJECTIVE: This study aimed to screen an immune-related gene (IRG) panel and develop a novel approach for diagnosing pulmonary arterial hypertension (PAH) utilizing bioinformatics and machine learning (ML).

Predicting sinonasal inverted papilloma attachment using machine learning: Current lessons and future directions.

American journal of otolaryngology
BACKGROUND: Hyperostosis is a common radiographic feature of inverted papilloma (IP) tumor origin on computed tomography (CT). Herein, we developed a machine learning (ML) model capable of analyzing CT images and identifying IP attachment sites.