AIMC Topic: Female

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A flexible machine learning Mendelian randomization estimator applied to predict the safety and efficacy of sclerostin inhibition.

American journal of human genetics
Mendelian randomization (MR) enables the estimation of causal effects while controlling for unmeasured confounding factors. However, traditional MR's reliance on strong parametric assumptions can introduce bias if these are violated. We describe a ma...

Implementing an artificial intelligence system into a diabetic eye screening programme in Tanzania.

Transactions of the Royal Society of Tropical Medicine and Hygiene
Tanzania has the highest age-adjusted prevalence of diabetes in sub-Saharan Africa. Diabetic retinopathy, a common complication, is a significant cause of vision loss; but with effective screening and treatment this often can be prevented. However, w...

The role of AI-enabled health systems in the Jordanian context: the case of digital contact tracing apps.

Journal of health organization and management
PURPOSE: Digital health or digital healthcare, is a broad, multidisciplinary concept that includes concepts from an intersection between technology and healthcare. Digital health applies digital transformation to the healthcare field, incorporating s...

Early Prediction of Septic Shock in Emergency Department Using Serum Metabolites.

Journal of the American Society for Mass Spectrometry
Early recognition of septic shock is crucial for improving clinical management and patient outcomes, especially in the emergency department (ED). This study conducted serum metabolomic profiling on ED patients diagnosed with septic shock (n = 32) and...

Redefining diagnostic lesional status in temporal lobe epilepsy with artificial intelligence.

Brain : a journal of neurology
Despite decades of advancements in diagnostic MRI, 30%-50% of temporal lobe epilepsy (TLE) patients remain categorized as 'non-lesional' (i.e. MRI negative) based on visual assessment by human experts. MRI-negative patients face diagnostic uncertaint...

Deep learning reveals pathology-confirmed neuroimaging signatures in Alzheimer's, vascular and Lewy body dementias.

Brain : a journal of neurology
Concurrent neurodegenerative and vascular pathologies pose a diagnostic challenge in the clinical setting, with histopathology remaining the definitive modality for dementia-type diagnosis. To address this clinical challenge, we introduce a neuropath...

Near-term prediction of sustained ventricular arrhythmias applying artificial intelligence to single-lead ambulatory electrocardiogram.

European heart journal
BACKGROUND AND AIMS: Accurate near-term prediction of life-threatening ventricular arrhythmias would enable pre-emptive actions to prevent sudden cardiac arrest/death. A deep learning-enabled single-lead ambulatory electrocardiogram (ECG) may identif...

From planning to prognosis: predicting renal function after minimally-invasive partial nephrectomy with artificial intelligence.

Minerva urology and nephrology
This study presents a machine learning model to predict renal function decline following minimally-invasive partial nephrectomy. Using a dataset of 556 patients treated between 2015 and 2023, the model incorporated patient, tumor, and intraoperative ...

Development and Validation of Quantile Regression Forests for Prediction of Reference Quantiles in Handgrip and Chair-Stand Test.

Journal of cachexia, sarcopenia and muscle
BACKGROUND: Muscle strength is one of the key components in the diagnosis of sarcopenia. The aim of this study was to train a machine learning model to predict reference values and percentiles for handgrip strength and chair-stand test (CST), in a la...