AIMC Topic: Machine Learning

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Whither bias goes, I will go: An integrative, systematic review of algorithmic bias mitigation.

The Journal of applied psychology
Machine learning (ML) models are increasingly used for personnel assessment and selection (e.g., resume screeners, automatically scored interviews). However, concerns have been raised throughout society that ML assessments may be biased and perpetuat...

Quantification of L-lactic acid in human plasma samples using Ni-based electrodes and machine learning approach.

Talanta
This work presents a robust strategy for quantifying overlapping electrochemical signatures originating from complex mixtures and real human plasma samples using nickel-based electrochemical sensors and machine learning (ML). This strategy enables th...

Synth-CLIP: Synthetic data make CLIP generalize better in data-limited scenarios.

Neural networks : the official journal of the International Neural Network Society
Prompt learning is a powerful technique that enables the transfer of Vision-Language Models (VLMs) like CLIP to downstream tasks. However, when the prompt-based methods are fine-tuned solely on base classes, they often struggle to generalize to novel...

DFedGFM: Pursuing global consistency for Decentralized Federated Learning via global flatness and global momentum.

Neural networks : the official journal of the International Neural Network Society
To tackle high communication costs and privacy issues in Centralized Federated Learning (CFL), Decentralized Federated Learning (DFL) is an alternative. However, a significant discrepancy exists between local updates and the expected global update, k...

Machine Learning Prediction of Early Recurrence in Gastric Cancer: A Nationwide Real-World Study.

Annals of surgical oncology
BACKGROUND: Patients with gastric cancer (GC) who experience early recurrence (ER) within 2 years postoperatively have poor prognoses. This study aimed to analyze and predict ER after curative surgery for patients with GC using machine learning (ML) ...

Machine learning-based forecast of Helmet-CPAP therapy failure in Acute Respiratory Distress Syndrome patients.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Helmet-Continuous Positive Airway Pressure (H-CPAP) is a non-invasive respiratory support that is used for the treatment of Acute Respiratory Distress Syndrome (ARDS), a severe medical condition diagnosed when symptoms like ...

Development of hybrid bionanocomposites of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) with zinc oxide and silicon-doped hydroxyapatite nanocrystals and machine learning for predicting dynamic mechanical properties.

International journal of biological macromolecules
The development of hybrid materials that integrate bioactive and antimicrobial properties within a biodegradable and biocompatible polymer matrix is a key focus in current biomedical research and applications. A significant research gap exists in the...

The role of industry 4.0 enabling technologies for predicting, and managing of algal blooms: Bridging gaps and unlocking potential.

Marine pollution bulletin
Recent advancements in data analytics, predictive modeling, and optimization have highlighted the potential of integrating algal blooms (ABs) with Industry 4.0 technologies. Among these innovations, digital twins (DT) have gained prominence, driven b...

Noninvasive machine-learning models for the detection of lesion-specific ischemia in patients with stable angina with intermediate stenosis severity on coronary CT angiography.

Physical and engineering sciences in medicine
This study proposed noninvasive machine-learning models for the detection of lesion-specific ischemia (LSI) in patients with stable angina with intermediate stenosis severity based on coronary computed tomography (CT) angiography. This single-center ...

Machine learning and confirmatory factor analysis show that buprenorphine alters motor and anxiety-like behaviors in male, female, and obese C57BL/6J mice.

Journal of neurophysiology
Buprenorphine is an opioid approved for medication-assisted treatment of opioid use disorder. Used off-label, buprenorphine has been reported to contribute to the clinical management of anxiety. Although human anxiety is a highly prevalent disorder, ...