AIMC Topic: Humans

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Liver MRI proton density fat fraction inference from contrast enhanced CT images using deep learning: A proof-of-concept study.

PloS one
Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common cause of chronic liver disease worldwide, affecting over 30% of the global general population. Its progressive nature and association with other chronic diseases make...

LGD_Net: Capsule network with extreme learning machine for classification of lung diseases using CT scans.

PloS one
Lung diseases (LGDs) are related to an extensive range of lung disorders, including pneumonia (PNEUM), lung cancer (LC), tuberculosis (TB), and COVID-19 etc. The diagnosis of LGDs is performed by using different medical imaging such as X-rays, CT sca...

Artificial intelligence in the diagnosis and management of dysphagia: a scoping review.

CoDAS
PURPOSE: This scoping review aimed to map and synthesize evidence on technological advancements using Artificial Intelligence in the diagnosis and management of dysphagia. We followed the PRISMA guidelines and those of the Joanna Briggs Institute, fo...

Unveiling the diagnostic and causal role of hyperlipidemia- and lipophagy-associated genes PLAUR, IVNS1ABP, and QKI in acute myocardial infarction.

International journal of cardiology
BACKGROUND: Hyperlipidemia (HLP) exacerbates myocardial cell injury by impairing lipophagy, a crucial lipid metabolic process, thereby increasing the risk of acute myocardial infarction (AMI). This study aims to identify biomarkers associated with HL...

Bioinspired multifunctional conductive hydrogel based on hydroxypropyl methyl cellulose for flexible sensors.

Carbohydrate polymers
Conductive hydrogels based on hydroxypropyl methyl cellulose (HPMC) show great potential in flexible sensors due to their low price and good biocompatibility. Nevertheless, the design of such conductive hydrogels with superior flexible deformability,...

Gastrointestinal bleeding detection on digital subtraction angiography using convolutional neural networks with and without temporal information.

Diagnostic and interventional radiology (Ankara, Turkey)
PURPOSE: Digital subtraction angiography (DSA) offers a real-time approach to locating lower gastrointestinal (GI) bleeding. However, many sources of bleeding are not easily visible on angiograms. This investigation aims to develop a machine learning...

AI-driven multi-modal framework for prognostic modeling in glioblastoma: Enhancing clinical decision support.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
OBJECTIVE: Glioblastoma (GBM) is the most aggressive malignant brain tumor, associated with poor prognosis and limited therapeutic options. Accurate prognostic modeling is essential for guiding personalized treatment strategies. However, existing mod...

Childhood trauma and adolescent anxiety: Uncovering emotion regulation pathways through integrated machine learning and traditional statistics.

Psychiatry research
Childhood trauma constitutes a significant risk factor for adolescent anxiety, with emotion regulation playing a critical role. This large-scale longitudinal study (N = 2461 at baseline, with external validation) examined differential relationships b...

Deep learning model enables the discovery of a novel BET inhibitor YD-851.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
BET inhibitor is a novel strategy in tumor therapy based on targeting epigenetic mechanism. In recent decades, dozens of clinical trials have been conducted to validate the potential efficacy of the first-generation BET inhibitors in refractory cance...

Accuracy and safety of ChatGPT-4o responses in rhinoplasty postoperative counseling: a panel-based study.

Acta oto-laryngologica
BACKGROUND: ChatGPT and other large language models have emerged as new tools for patient education, yet their clinical safety and reliability remain unclear.