AIMC Topic: Aged

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Explainable machine learning model for predicting the risk of significant liver fibrosis in patients with diabetic retinopathy.

BMC medical informatics and decision making
BACKGROUND: Diabetic retinopathy (DR), a prevalent complication in patients with type 2 diabetes, has attracted increasing attention. Recent studies have explored a plausible association between retinopathy and significant liver fibrosis. The aim of ...

Predicting malignancy in breast lesions: enhancing accuracy with fine-tuned convolutional neural network models.

BMC medical imaging
BACKGROUND: This study aims to explore the accuracy of Convolutional Neural Network (CNN) models in predicting malignancy in Dynamic Contrast-Enhanced Breast Magnetic Resonance Imaging (DCE-BMRI).

Impact of different nephrectomy types on M0 renal cell carcinoma outcomes in a propensity score matching and deep learning study.

Scientific reports
There are few analyses comparing complete nephrectomy with resection of the renal parenchyma only (CN) or radical nephrectomy that includes simultaneous resection of the parenchyma, affected perirenal fascia, perirenal fat, and ureter (RN) relative t...

Evaluating the effectiveness of AI-powered UrologiQ's in accurately measuring kidney stone volume in urolithiasis patients.

Urolithiasis
Kidney stones and urolithiasis are kidney diseases that have a significant impact on health and well-being, and their incidence is increasing annually owing to factors such as age, sex, ethnicity, and geographical location. Accurate identification an...

A deep learning-based method for assessing tricuspid regurgitation using continuous wave Doppler spectra.

Scientific reports
Transthoracic echocardiography (TTE) is widely recognized as one of the principal modalities for diagnosing tricuspid regurgitation (TR). The diagnostic procedures associated with conventional methods are intricate and labor-intensive, with human err...

Gender-specific aspects of socialisation and risk of cardiovascular disease among community-dwelling older adults: a prospective cohort study using machine learning algorithms and a conventional method.

Journal of epidemiology and community health
BACKGROUND: Gender influences cardiovascular disease (CVD) through norms, social relations, roles and behaviours. This study identified gender-specific aspects of socialisation associated with CVD.

Enhancing type 2 diabetes mellitus prediction by integrating metabolomics and tree-based boosting approaches.

Frontiers in endocrinology
BACKGROUND: Type 2 diabetes mellitus (T2DM) is a global health problem characterized by insulin resistance and hyperglycemia. Early detection and accurate prediction of T2DM is crucial for effective management and prevention. This study explores the ...

Explainable machine learning for early prediction of sepsis in traumatic brain injury: A discovery and validation study.

PloS one
BACKGROUND: People with traumatic brain injury (TBI) are at high risk for infection and sepsis. The aim of the study was to develop and validate an explainable machine learning(ML) model based on clinical features for early prediction of the risk of ...

Grade prediction of lesions in cerebral white matter using a convolutional neural network.

PloS one
We established a diagnostic method for cerebral white matter lesions using MRI images and examined the relationship between the MRI images and the medical checkup data. There were approximately 25 MRI images for each patient's head, from the top of t...

Postoperative Karnofsky performance status prediction in patients with IDH wild-type glioblastoma: A multimodal approach integrating clinical and deep imaging features.

PloS one
BACKGROUND AND PURPOSE: Glioblastoma is a highly aggressive brain tumor with limited survival that poses challenges in predicting patient outcomes. The Karnofsky Performance Status (KPS) score is a valuable tool for assessing patient functionality an...