AIMC Topic: Humans

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A novel deep learning system for STEMI prognostic prediction from multi-sequence cardiac magnetic resonance.

Science bulletin
ST-elevation myocardial infarction (STEMI) remains a leading cause of cardiovascular morbidity and mortality worldwide, and accurate early risk stratification is critical for implementing precision therapies in clinical practice. However, existing cl...

Efficient Hybrid Hierarchical Clustering with Incremental Silhouette Score for Large, Noisy Datasets.

International journal of neural systems
This paper introduces a comprehensive framework for clustering analysis, centered on a novel incremental silhouette score calculation designed specifically for hierarchical clustering. This innovative method significantly reduces the computational co...

C-reactive protein-triglyceride glucose index in predicting three-vessel coronary artery disease risk: a retrospective study using machine learning approaches.

Annals of medicine
BACKGROUND: Three-vessel coronary artery disease (TVD) is a severe subtype of coronary heart disease, strongly associated with inflammation and metabolic dysfunction. The C-reactive protein-triglyceride glucose index (CTI), an integrated measure of i...

Variation in the efficiency of English general practices and associated factors: A cross-sectional study of 5069 general practices.

The European journal of general practice
BACKGROUND: Healthcare demand in English general practice exceeds supply, necessitating practice efficiency. To our knowledge, no study has explored factors associated with practice efficiency in England using a quality-adjusted output.

Machine learning-based preliminary screening tool for clinical pregnancy prediction: towards management of IVF/ICSI stages.

Annals of medicine
BACKGROUND: Accurate prediction of pregnancy outcomes in assisted reproductive technology (ART) remains a clinical challenge due to the complexity and heterogeneity of IVF/ICSI cycles. Existing models often focus on isolated treatment stages and rely...

Machine learning combined with body composition predicts surgical difficulty in mid-low rectal cancer surgery.

Annals of medicine
BACKGROUND: This study sought to identify critical body composition characteristics associated with surgical difficulty in Laparoscopic Total Mesorectal Excision (LaTME) and to develop and validate an interpretable machine learning model using body c...

Analysis of Retracted Publications on Artificial Intelligence: Trends, Ethical Concerns, and Scientific Integrity.

Journal of Korean medical science
BACKGROUND: Artificial intelligence (AI) has promoted progress across various fields. The number of papers regarding AI has risen in recent years. This study examines retracted publications regarding AI by analyzing trends, journals, and reasons.

An interpretable delta ultrasound radiomics model for predicting live birth outcomes in single vitrified-warmed blastocyst transfer.

Journal of ovarian research
OBJECTIVE: To develop and validate an interpretable delta ultrasound radiomics model for predicting live birth following single vitrified-warmed blastocyst transfer (SVBT).

Automated quantification of Ki-67 expression in breast cancer from H&E-stained slides using a transformer-based regression model.

Breast cancer research : BCR
BACKGROUND: Accurate quantification of the Ki-67 proliferation index is essential for breast cancer prognosis and treatment planning. Current automated methods, including classical and deep learning approaches based on cell detection or segmentation,...

Effect of upper-limb robot-assisted therapy combined with pneumatic gloves on upper limb function in young and middle-aged stroke patients: a pilot randomized controlled trial.

Journal of neuroengineering and rehabilitation
BACKGROUND: This study aimed to evaluate the effects of an end-effector-type upper-limb robot-assisted therapy (UL-RAT) combined with pneumatic gloves (PGs) on improving upper limb function in young and middle-aged stroke patients.