AIMC Topic: Middle Aged

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Artificial intelligence-assisted endoscopic ultrasound diagnosis of esophageal subepithelial lesions.

Surgical endoscopy
BACKGROUND: Endoscopic ultrasound (EUS) is one of the most accurate methods for determining the originating layer of subepithelial lesions (SELs). However, the accuracy is greatly influenced by the expertise and proficiency of the endoscopist. In thi...

Enhancing osteoporosis risk prediction using machine learning: A holistic approach integrating biomarkers and clinical data.

Computers in biology and medicine
Osteoporosis (OP) affects approximately 18 % of the global population, with osteoporosis-associated fractures impacting up to 37 million people annually. While dual-energy X-ray absorptiometry (DXA) remains the gold standard for diagnosis, its limita...

Effects of an artificial intelligence-based exercise program on pain intensity and disability in patients with neck pain compared with group exercise therapy: A cohort study.

Journal of bodywork and movement therapies
OBJECTIVES: This study compares the effects of an artificial intelligence app-based exercise program with group exercise therapy on pain intensity and neck-related disability in patients with neck pain.

Automated machine learning model for predicting anastomotic strictures after esophageal cancer surgery: a retrospective cohort study.

Surgical endoscopy
BACKGROUND: Anastomotic strictures (AS) frequently occurs in patients following esophageal cancer surgery, significantly affecting their long-term quality of life. This study aims to develop a machine learning model to predict high-risk AS, enabling ...

Integrating Machine Learning and Dynamic Digital Follow-up for Enhanced Prediction of Postoperative Complications in Bariatric Surgery.

Obesity surgery
BACKGROUND: Traditional risk models, such as POSSUM and OS-MS, have limited accuracy in predicting complications after bariatric surgery. Machine learning (ML) offers new opportunities for personalized risk assessment by incorporating artificial inte...

Sharing patient technology preferences with care networks: Stakeholders' views of the "Let's Talk Tech" decision aid for dementia care.

Journal of Alzheimer's disease : JAD
BackgroundLet's Talk Tech (LTT) is a self-administered web intervention for people with memory loss and their care partners that supports decision-making about digital health technologies. In past work, dyads wanted to share LTT preference reports wi...

DeepValve: The first automatic detection pipeline for the mitral valve in Cardiac Magnetic Resonance imaging.

Computers in biology and medicine
Mitral valve (MV) assessment is key to diagnosing valvular disease and to addressing its serious downstream complications. Cardiac magnetic resonance (CMR) has become an essential diagnostic tool in MV disease, offering detailed views of the valve st...

Needs of bereaved families of patients with cancer towards artificial intelligence in palliative care: A web-based survey.

European journal of oncology nursing : the official journal of European Oncology Nursing Society
PURPOSE: Artificial intelligence (AI) systems in palliative care have garnered attention and popularity in recent years. Understanding patient and family needs is crucial for developing and implementing AI systems in palliative care. Few studies in p...

Evaluating artificial intelligence in decision-making for surgical treatment of benign breast conditions.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS
INTRODUCTION: Determining the ideal surgical strategy for breast pathologies can sometimes be challenging, in particular if personalized solutions are required. Moreover, acquiring the necessary expertise takes years. Artificial intelligence (AI) may...