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The implementation of artificial intelligence in serial monitoring of post gamma knife vestibular schwannomas: A pilot study.

BACKGROUND: Vestibular schwannomas (VS) are benign tumors that can lead to hearing loss, balance iss...

Prediction of post stroke depression with machine learning: A national multicenter cohort study.

OBJECTIVE: Post-stroke depression (PSD) is a common psychiatric complication following stroke, with ...

Pushing the Limit of Post-Training Quantization.

Recently, post-training quantization (PTQ) has become the de facto way to produce efficient low-prec...

[Progress in neoadjuvant immunotherapy for locally advanced rectal cancer].

Neoadjuvant chemoradiotherapy (NACRT) is the standard treatment for locally advanced rectal cancer (...

Attention Regulation Among Sleep-Deprived Air-Force Pilots.

Short sleep duration is associated with adverse physical and mental events. However, it is quite cha...

From Acquisition to Prognosis: The Role of AI in Cardiac Magnetic Resonance Imaging Evaluation of Ischemic Cardiomyopathy.

Acute and chronic ischemic cardiomyopathy (ICM) still represents a leading cause of morbidity and mo...

Drug-Drug interactions and special considerations in breast cancer patients treated with CDK4/6 inhibitors: A comprehensive review.

Cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) have reshaped the treatment paradigm of hormone rec...

Attention to early stages: predicting acute kidney injury in a post cardiosurgical ICU setting using an inclusive time-to-event model.

BACKGROUND: Acute kidney injury (AKI) is a critical complication in intensive care units (ICUs) that...

AI-based prediction of left bundle branch block risk post-TAVI using pre-implantation clinical parameters.

BACKGROUND AND AIMS: Transcatheter Aortic Valve Implantation (TAVI) has revolutionized the treatment...

BenchXAI: Comprehensive benchmarking of post-hoc explainable AI methods on multi-modal biomedical data.

The increasing digitalization of multi-modal data in medicine and novel artificial intelligence (AI)...

Establishment of a machine learning-based prediction framework to assess trade-offs in decisions that affect post-HCT outcomes.

In this study, we propose a conceptual framework of decision support tools, built upon machine learn...

CR-deal: Explainable Neural Network for circRNA-RBP Binding Site Recognition and Interpretation.

circRNAs are a type of single-stranded non-coding RNA molecules, and their unique feature is their c...

On the State of NLP Approaches to Modeling Depression in Social Media: A Post-COVID-19 Outlook.

Computational approaches to predicting mental health conditions in social media have been substantia...

Automated diagnosis for extraction difficulty of maxillary and mandibular third molars and post-extraction complications using deep learning.

Optimal surgical methods require accurate prediction of extraction difficulty and complications. Alt...

Machine learning analysis of factors contributing to hypotension after lumbosacral epidural anaesthesia in dogs undergoing abdominal surgery.

The incidence of hypotension after a lumbosacral epidural in dogs depends on the volume of local ana...

Machine learning in colorectal polyp surveillance: A paradigm shift in post-endoscopic mucosal resection follow-up.

Colorectal cancer remains a major health concern, with colorectal polyps as key precursors. Endoscop...

Unsupervised post-training learning in spiking neural networks.

The human brain is a dynamic system that is constantly learning. It employs a combination of various...

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