AIMC Topic: Middle Aged

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Artificial inteligence reading of cystometric traces provides good correlation with human diagnosis.

World journal of urology
AIM: Urodynamic studies are essential for diagnosing lower urinary tract dysfunction but are expert-dependent and time-consuming. Artificial intelligence (AI), notably machine learning (ML) and deep learning (DL) may help automate and standardize int...

Assessing the Accuracy of Artificial Intelligence in Detecting Intracranial Aneurysms in a Clinical Setting Relative to Neuroradiologists.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Intracranial aneurysms (IAs), detected in 2%-5% of the population, represent a major health care issue because ruptured aneurysms with resultant hemorrhage are associated with severe morbidity or mortality. With the increasing...

An automated classification of brain white matter inherited disorders (Leukodystrophy) using MRI image features.

Biomedical physics & engineering express
Leukodystrophies are a group of inherited disorders that predominantly and selectively affect the white matter of the central nervous system. Their overlapping clinical and imaging manifestations make a timely and accurate diagnosis challenging. In t...

Both Infarcted and Noninfarcted Brain Regions Contribute to Deep Learning-Based MRI Prediction of Acute Stroke Outcome.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Predicting long-term clinical outcomes based on early acute ischemic stroke (AIS) information would be useful for many reasons, including patient counseling and clinical trial execution. This study investigates how different r...

Artificial Intelligence-Driven Detection of Large Vessel Occlusions on NCCT: A Multi-Institutional Study.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Imaging triage of stroke patients is primarily based on perfusion imaging. Simplified triage based on non-contrast CT are limited (NCCT). To evaluate the predictive capability of a deep learning algorithm, "Triage Stroke" (Bra...

Abnormal brain network reconfiguration in neuropsychiatric disorders across cognitive decline, Depression, and Schizophrenia.

PloS one
OBJECTIVE: Neuropsychiatric disorders are characterized by high complexity and comorbidity, imposing a substantial burden on both patients and society. However, their elusive pathogenic mechanisms impede accurate clinical diagnosis and effective inte...

Temporal shifts in prognostic factors for 90- and 180-day outcomes after stroke thrombolysis: A machine learning analysis.

PloS one
INTRODUCTION: Prognostication at 90 and 180 days after thrombolysis for acute ischemic stroke (AIS) is critical, yet the temporal evolution of key predictors remains inadequately understood. The utility of machine learning for systematically comparin...

ECG-based deep learning for chronic kidney disease detection and cardiovascular risk prediction.

BMC medical informatics and decision making
BACKGROUND: Chronic kidney disease (CKD) is a global health burden with low awareness among both patients and healthcare providers. Deep learning models (DLMs) have shown promise in interpreting electrocardiograms (ECGs) for various disease and may o...

Foundation model based prediction of lung cancer survival using temporal changes in dual time point CT scans.

Scientific reports
Lung cancer remains a significant cause of mortality, with non-small cell lung cancer (NSCLC) representing most cases. Currently, clinical data based models fall short in predicting survival while more advanced deep learning based image models requir...