Geriatrics

Novel machine learning framework for multidimensional biological age estimation reveals heterogeneous aging of organ systems.

OBJECTIVE: Existing biological age (BA) models often oversimplify aging's complexity, offering single-dimensional metrics. However, these fail to capture the critical heterogeneity of aging across organs.. This study aims to develop a machine learning-based unified framework to assess and interpret multi-organ biological aging comprehensively. METHOD: Using data from UK Biobank participants, we tr...

Clinical Application of an AI-Driven Framework for Accurate Endometrial Thickness Measurement in Transvaginal Ultrasound.

OBJECTIVE: This study aims to develop an AI-based framework for automatic endometrial thickness (ET) measurement in transvaginal ultrasound (TVUS) based on a large dataset and evaluate its performance from various clinical perspectives. METHODS: A dataset of 9850 ultrasound images from 5110 cases at Shenzhen Guangming District People's Hospital (2019-2023) was retrospectively included for training...

An explainable machine learning model predicts 30-day readmission after vertebral augmentation.

Osteoporotic vertebral compression fracture (OVCF) patients face high 30-day readmission risks after vertebral augmentation procedures (VAPs). Using e...

A Multi-instance Learning Network with Prototype-instance Adversarial Contrastive for Cervix Pathology Grading.

The pathological grading of cervical squamous cell carcinoma (CSCC) is a fundamental and important index in tumor diagnosis. Pathologists tend to focu...

OCT-PRO: A Multimodal Model Integrating OCT and Clinical Traits to Predict Postoperative Outcomes in Cataract Patients.

PURPOSE: To develop and validate OCT-PRO, a multimodal machine learning model integrating OCT images and clinical traits to predict postoperative visu...

SET-DGCN: An end-to-end electroencephalography-based fatigue detection method for young drivers.

Driver fatigue poses a critical threat to global road safety, particularly among young drivers. Nevertheless, policy-level interventions remain fragme...

Machine learning-assisted high-performance immunoSERS platform using silk fibroin as a natural etching mask for early diagnosis of Alzheimer's disease.

Early and accurate diagnosis of Alzheimer's disease (AD) is a major stride toward pharmacological interventions to delay the onset or progression of t...

Data-Driven Detection of Subclinical Keratoconus via Semi-Supervised Clustering of Multidimensional Corneal Biomarkers.

PURPOSE: To objectively identify subclinical keratoconus (SKC) from a large sample of healthy and keratoconus (KC) patients via a data-driven framewor...

CellApop: A knowledge-guided decoupled distillation framework for label-efficient apoptotic cell segmentation and dynamic analysis in brightfield microscopy.

BACKGROUND AND OBJECTIVE: Conventional apoptosis detection methods primarily depend on fluorescence staining, which is labor-intensive, potentially cy...

Fully automated multi-sequence detection and alignment of focal liver lesions in dynamic contrast-enhanced MRI.

OBJECTIVES: To validate an artificial intelligence (AI) method for fully automated detection and alignment of focal liver lesions (FLLs) in multi-sequ...

Combination of artificial intelligence and chest computed tomography to assess bone mineral density.

OBJECTIVES: To evaluate the diagnostic accuracy of artificial intelligence-assisted opportunistic chest CT for osteoporosis/osteopenia screening in a ...

End-to-end design of multi-functional acoustic holograms via heterogeneous physics constraints.

Acoustic holograms offer precise three-dimensional control of sound fields with immense potential for non-invasive therapies and contactless manipulat...

The ICeX framework: Brain age estimation from thalamic nuclei with conformalized and eXplainable random forest regression.

BACKGROUND AND OBJECTIVE: Accurate estimation of brain age is essential to identify deviations from typical aging trajectories, which may signal early...

Advancing osteoporosis opportunistic screening: multicenter validation of a deep learning algorithm using abdominal CT scans.

OBJECTIVES: To develop and do multicenter validation on an algorithm that screens for osteoporosis from abdominal CTs. METHODS: This is a diagnostic a...

Systematic post-translational modification genome wide identifies therapeutic targets for Alzheimer's disease: evidence from multi-cohort analysis.

BACKGROUND: The rapid increase in the incidence of Alzheimer's disease (AD) has raised concerns, given its profound effects on both society and the ec...

Nanomotion-based technology for rapid antibiotic susceptibility testing among adult patients admitted to a tertiary-care hospital with Gram-negative bacteraemia: a prospective, single arm, comparative diagnostic accuracy study.

OBJECTIVE: Investigate performances and turnaround time of Resistell Phenotech antibiotic susceptibility testing (AST), a device using the new nanomot...

Probabilistic maps of white matter hyperintensity in a Chinese aging cohort and application for clinical diagnosis.

OBJECTIVES: White matter hyperintensities (WMH) are abnormalities in brain imaging that contribute to cognitive decline and diseases. This study aimed...

Machine learning-enabled assessment of risk of drug-induced QT prolongation at the time of prescribing.

BACKGROUND: Many medications are associated with long QTc. Current long QTc predictors have limited generalizability and/or modest performance. OBJECT...

Application of Machine Learning Based on Ultrasonic RF Time Series and 2D Image Features in the Diagnosis of BI-RADS 4A Lesions of Breast.

OBJECTIVES: This study aimed to develop and validate machine-learning (ML) models that integrate ultrasonic radiofrequency (RF) time-series signals wi...

Robotic thoracic surgery: what is different in anesthesia?

PURPOSE OF REVIEW: Robotic-assisted thoracic surgery (RATS) has emerged as a transformative approach in thoracic surgery, enabling enhanced precision ...