AIMC Topic: Databases, Factual

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Machine learning to predict periprosthetic joint infections following primary total hip arthroplasty using a national database.

Archives of orthopaedic and trauma surgery
INTRODUCTION: Periprosthetic joint infection (PJI) following total hip arthroplasty (THA) remains a devastating complication for patients and surgeons. Given the implications of these infections and the current paucity of risk calculators utilizing m...

Comparative analysis of kidney function prediction: traditional statistical methods vs. deep learning techniques.

Clinical and experimental nephrology
BACKGROUND: Chronic kidney disease (CKD) represents a significant public health challenge, with rates consistently on the rise. Enhancing kidney function prediction could contribute to the early detection, prevention, and management of CKD in clinica...

Extracting organs of interest from medical images based on convolutional neural network with auxiliary and refined constraints.

Scientific reports
Accurately extracting organs from medical images provides radiologist with more comprehensive evidences to clinical diagnose, which offers up a higher accuracy and efficiency. However, the key to achieving accurate segmentation lies in abundant clues...

A Deep and Interpretable Learning Approach for Long-Term ECG Clinical Noise Classification.

IEEE transactions on bio-medical engineering
OBJECTIVE: In Long-Term Monitoring (LTM), noise significantly impacts the quality of the electrocardiogram (ECG), posing challenges for accurate diagnosis and time-consuming analysis. The clinical severity of noise refers to the difficulty in interpr...

Generative Adversarial Networks With Radiomics Supervision for Lung Lesion Generation.

IEEE transactions on bio-medical engineering
Data-driven methods for lesion generation are quickly emerging due to the need for realistic imaging targets for image quality assessment and virtual clinical trials. We proposed a generative adversarial network (GAN) architecture for conditional gen...

BiomedRAG: A retrieval augmented large language model for biomedicine.

Journal of biomedical informatics
Retrieval-augmented generation (RAG) involves a solution by retrieving knowledge from an established database to enhance the performance of large language models (LLM). , these models retrieve information at the sentence or paragraph level, potential...

Clinical validation of artificial intelligence-based single-subject morphometry without normative reference database.

Journal of Alzheimer's disease : JAD
BACKGROUND: Single-subject voxel-based morphometry (VBM) is a powerful technique for reader-independent detection of brain atrophy in structural magnetic resonance imaging (MRI) to support the (differential) diagnosis and staging of neurodegenerative...

Mortality prediction after major surgery in a mixed population through machine learning: a multi-objective symbolic regression approach.

Anaesthesia
INTRODUCTION: Understanding 1-year mortality following major surgery offers valuable insights into patient outcomes and the quality of peri-operative care. Few models exist that predict 1-year mortality accurately. This study aimed to develop a predi...