AIMC Topic: Middle Aged

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Risk Stratification of Dengue Cases Requiring Hospitalization.

Journal of medical virology
Dengue pathogenesis involves immune-driven inflammation that contributes to severe disease progression. This study assessed a machine learning model to identify a minimal, yet highly predictive biomarker set, aiming to support clinical decision-makin...

A multi-stage 3D convolutional neural network algorithm for CT-based lung segment parcellation.

Journal of applied clinical medical physics
BACKGROUND: Current approaches to lung parcellation utilize established fissures between lobes to provide estimates of lobar volume. However, deep learning segment parcellation provides the ability to better assess regional heterogeneity in ventilati...

Brain Age Prediction: Deep Models Need a Hand to Generalize.

Human brain mapping
Predicting brain age from T1-weighted MRI is a promising marker for understanding brain aging and its associated conditions. While deep learning models have shown success in reducing the mean absolute error (MAE) of predicted brain age, concerns abou...

The Silent Transformation of Stereotactic Brain Biopsies After the Introduction of Robotics.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: In frame-based stereotaxy, the design of the frame limits trajectory selection, e.g., to the temporal lobe and posterior fossa. We hypothesise that frame-less neuronavigation and robotic technology might have expanded these stereotactic c...

A model based on artificial intelligence for the prediction, prevention and patient-centred approach for non-communicable diseases related to metabolic syndrome.

European journal of public health
Metabolic syndrome (MetS) is related to non-communicable diseases (NCDs) such as type 2 diabetes (T2D), metabolic-associated steatotic liver disease (MASLD), atherogenic dyslipidaemia (ATD), and chronic kidney disease (CKD). The absence of reliable t...

Multiomics and Machine Learning Identify Immunometabolic Biomarkers for Active Tuberculosis Diagnosis Against Nontuberculous Mycobacteria and Latent Tuberculosis Infection.

Journal of proteome research
This study utilized multiomics combined with a comprehensive machine learning-based predictive modeling approach to identify, validate, and prioritize circulating immunometabolic biomarkers in distinguishing tuberculosis (TB) from nontuberculous myco...

Circulating Proteomic Panels for Noninvasive Diagnosis and Prognostication of Thromboangiitis Obliterans.

Journal of proteome research
Thromboangiitis obliterans (TAO) is often diagnosed late and characterized by high amputation rates. TAO-specific early diagnostic and disease-staging biomarkers are urgently needed. A staged mass spectrometry (MS)-based discovery-verification-valida...

Validation of the ACS-NSQIP surgical risk calculator for patients with paraoesophageal hernias undergoing robotic repair.

Surgical endoscopy
BACKGROUND: The National Surgical Quality Improvement Program (NSQIP) American College of Surgeons (ACS) risk calculator is a validated method of predicting postoperative complications that was recently updated to a machine-learning structure. The ob...

Optimizing surgical efficiency: predicting case duration of common general surgery procedures using machine learning.

Surgical endoscopy
BACKGROUND: Accurate prediction of surgical duration is critical to optimizing use of operating room resources. Currently, cases are scheduled using subjective estimates of length by surgeons, relying heavily on prior experience. This study aims to d...

Development and validation of a SOTA-based system for biliopancreatic segmentation and station recognition system in EUS.

Surgical endoscopy
BACKGROUND: Endoscopic ultrasound (EUS) is a vital tool for diagnosing biliopancreatic disease, offering detailed imaging to identify key abnormalities. Its interpretation demands expertise, which limits its accessibility for less trained practitione...