Cytomorphological analysis of the bone marrow aspirate (BMA) is pivotal for the diagnostic workup of a broad range of hematological disorders. However, this skill is error prone, highly complex, and time consuming. Deep learning-based models for the ...
The human skin can reliably capture a wide range of multimodal data over a large surface while providing a soft interface. Artificial technologies using microelectromechanical systems (MEMS) can emulate these biological functions but present numerous...
To develop and validate a machine learning prediction model for 28-day all-cause mortality in patients with alcoholic cirrhosis using data from the MIMIC-IV database. The data of 2134 patients diagnosed with alcoholic cirrhosis (AC) were obtained fro...
BACKGROUND: Postoperative complications in colorectal surgery can significantly impact patient outcomes and healthcare costs. Accurate prediction of these complications enables targeted perioperative management, improving patient safety and optimizin...
BACKGROUND: Next-generation sequencing (NGS) has become a cornerstone of treatment for lung cancer and is recommended in current treatment guidelines for patients with advanced or metastatic disease.
Machine learning should be integrated into medical curricula to prepare physicians-in-training for 21st-century practice conditions. This comment proposes practical implementation strategies that build upon existing educational frameworks by drawing ...
In the field of healthcare, artificial intelligence (AI)-assisted solutions can be viewed with anxiety or apprehension, thus transparency and trust-building are essential. AI is often invisible (and potentially undisclosed) to users, violating the et...
Medical image reconstruction aims to generate high-quality images from incompletely sampled raw sensor data, which poses an ill-posed inverse problem. Traditional iterative reconstruction methods rely on prior information to empirically construct reg...
. Common spatial patterns (CSPs) has been established as a powerful feature extraction method in EEG signal processing with machine learning, but it has shortcomings including sensitivity to noise and rigidity in the value of the weights. Our goal wa...
R-loops are three-stranded RNA and DNA hybrid structures that often occur in the genome and play important roles in a variety of cellular processes from bacteria to mammals. Sequencing methods profiling R-loops genome-wide have revealed that they can...
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