AIMC Topic: Aged

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Selecting measures of visual function to classify diabetic retinopathy status: a cross-sectional study.

BMJ open ophthalmology
AIM: To identify combinations of up to three visual function tests with the best performance for classifying diabetic retinopathy (DR) severity stage. To describe in detail the measurements from a comprehensive set of visual function tests. METHODS: ...

Translational and real-world evidence of trastuzumab biosimilar CT-P6 plus pertuzumab in neoadjuvant HER2-positive early breast cancer.

Breast cancer research and treatment
BACKGROUND: Data on neoadjuvant treatment with trastuzumab biosimilars, particularly CT-P6, in combination with pertuzumab, are limited. This study evaluates the efficacy, tolerability, and immunogenicity of CT-P6 plus pertuzumab and chemotherapy, in...

Autonomous conversational agents for loneliness, social isolation, depression, and anxiety in older people without cognitive impairment: Systematic review and meta-analysis.

Psychological medicine
Loneliness is a major psychological challenge in older adulthood, contributing to increased risks of depression, anxiety, and mortality. Conversational agents - technologies that interact with users via natural language - have emerged as potential to...

Deep learning detection and classification of fungal and non-fungal calcifications on paranasal sinus CT imaging.

PloS one
This study aimed to develop and evaluate a deep learning algorithm for detecting and classifying intrasinus calcifications on paranasal sinus (PNS) computed tomography (CT) for the diagnosis of fungal sinusitis and differentiation of fungal and non-f...

Machine learning-based risk modeling for safety-focused learning curve assessment in robotic left-sided colorectal cancer surgery.

Journal of robotic surgery
The transition from laparoscopic to robotic surgery for left-sided colorectal cancer raises safety concerns during the learning curve, particularly when complex cases are preferentially selected for the robotic platform. We evaluated a machine learni...

Preoperative CT imaging and machine learning models for predicting ureteral access sheath placement success in non-stented patients with ureteral calculi: a retrospective cohort study.

World journal of urology
OBJECTIVE: This study aims to both develop and evaluate a predictive model for ureteral access sheath(UAS)placement success using preoperative CT-based 3D ureteral imaging and machine learning techniques. Specifically, it investigates the impact of u...

Machine learning for triage of strokes with large vessel occlusion using photoplethysmography biomarkers.

Physiological measurement
Objective.Large vessel occlusion (LVO) stroke presents a major challenge in clinical practice due to the potential for poor outcomes with delayed treatment. Treatment for LVO involves highly specialized care, in particular endovascular thrombectomy, ...

Predicting the progression of difficult-to-treat rheumatoid arthritis by a machine learning scoring system, from the FIRST registry.

RMD open
OBJECTIVES: This study aimed to develop and validate a prediction model for the future progression of difficult-to-treat rheumatoid arthritis (D2T RA) and support the precise use of biologic and targeted synthetic disease-modifying antirheumatic drug...

Development and external validation of machine learning approaches for risk prediction of cardiovascular disease in individuals with schizophrenia: a nationwide Swedish and Danish study.

BMJ mental health
BACKGROUND: Currently available cardiovascular disease (CVD) risk prediction tools may underestimate the risk in individuals with schizophrenia. OBJECTIVE: To develop and externally validate 5-year CVD risk prediction models for people with schizophr...