AIMC Topic: Algorithms

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Proactive vs. passive algorithmic ethics practices in healthcare: the moderating role of healthcare engagement type in patients' responses.

BMC medical ethics
BACKGROUND: Artificial intelligence (AI) is transforming healthcare, but concerns about algorithmic biases and ethical challenges hinder patient acceptance. This study examined the effects of proactive versus passive algorithmic ethics practices on p...

Extracting Residue Solvent Exposure from Covalent Labeling Data with Machine Learning: A Hybrid Approach for Protein Structure Prediction.

Journal of the American Society for Mass Spectrometry
Hydroxyl radical protein footprinting (HRPF) coupled with mass spectrometry yields information about residue solvent exposure and protein topology. However, data from these experiments are sparse and require computational interpretation to generate u...

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...

A deep learning-based method for predicting the frequency classes of drug side effects based on multi-source similarity fusion.

Bioinformatics (Oxford, England)
MOTIVATION: Drug side effects refer to harmful or adverse reactions that occur during drug use, unrelated to the therapeutic purpose. A core issue in drug side effect prediction is determining the frequency of these drug side effects in the populatio...

CrossAttOmics: multiomics data integration with cross-attention.

Bioinformatics (Oxford, England)
MOTIVATION: Advances in high throughput technologies enabled large access to various types of omics. Each omics provides a partial view of the underlying biological process. Integrating multiple omics layers would help have a more accurate diagnosis....

The signed two-space proximity model for learning representations in protein-protein interaction networks.

Bioinformatics (Oxford, England)
MOTIVATION: Accurately predicting complex protein-protein interactions (PPIs) is crucial for decoding biological processes, from cellular functioning to disease mechanisms. However, experimental methods for determining PPIs are computationally expens...

Hyperparameter Control Using Fuzzy Logic: Evolving Policies for Adaptive Fuzzy Particle Swarm Optimization Algorithm.

Evolutionary computation
Heuristic optimization methods such as particle swarm optimization (PSO) depend on their parameters to achieve optimal performance on a given class of problems. Some modifications of heuristic algorithms aim at adapting those parameters during the op...

Segmentation of Leukoaraiosis on Noncontrast Head CT Using CT-MRI Paired Data Without Human Annotation.

Brain and behavior
OBJECTIVE: Evaluating leukoaraiosis (LA) on CT is challenging due to its low contrast and similarity to parenchymal gliosis. We developed and validated a deep learning algorithm for LA segmentation using CT-MRIFLAIR paired data from a multicenter Kor...

A Bayesian Approach to the G-Formula via Iterative Conditional Regression.

Statistics in medicine
In longitudinal observational studies with time-varying confounders, the generalized computation algorithm formula (g-formula) is a principled tool to estimate the average causal effect of a treatment regimen. However, the standard non-iterative g-fo...

A Machine Learning Algorithm to Estimate the Probability of a True Scaphoid Fracture After Wrist Trauma.

The Journal of hand surgery
PURPOSE: To identify predictors of a true scaphoid fracture among patients with radial wrist pain following acute trauma, train 5 machine learning (ML) algorithms in predicting scaphoid fracture probability, and design a decision rule to initiate adv...