AIMC Topic: Machine Learning

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Advancing neural network calibration: The role of gradient decay in large-margin Softmax optimization.

Neural networks : the official journal of the International Neural Network Society
This study introduces a novel hyperparameter in the Softmax function to regulate the rate of gradient decay, which is dependent on sample probability. Our theoretical and empirical analyses reveal that both model generalization and calibration are si...

Optimizing vancomycin dosing in pediatrics: a machine learning approach to predict trough concentrations in children under four years of age.

International journal of clinical pharmacy
BACKGROUND: Vancomycin trough concentration is closely associated with clinical efficacy and toxicity. Predicting vancomycin trough concentrations in pediatric patients is challenging due to significant inter-individual variability and rapid physiolo...

Global Distribution of Mercury in Foliage Predicted by Machine Learning.

Environmental science & technology
Foliar assimilation of elemental mercury (Hg) from the atmosphere plays a critical role in the global Hg biogeochemical cycle, leading to atmospheric Hg removal and soil Hg insertion. Recent studies have estimated global foliar Hg assimilation; howev...

Assessing the anticholinergic cognitive burden classification of putative anticholinergic drugs using drug properties.

British journal of clinical pharmacology
AIMS: This study evaluated the use of machine learning to leverage drug absorption, distribution, metabolism and excretion (ADME) data together with physicochemical and pharmacological data to develop a novel anticholinergic burden scale and compare ...

Machine learning algorithms integrate bulk and single-cell RNA data to unveil oxidative stress following intracerebral hemorrhage.

International immunopharmacology
BACKGROUND: Increased oxidative stress (OS) activity following intracerebral hemorrhage (ICH) had significantly impacting patient prognosis. Identifying optimal genes associated with OS could enhance the understanding of OS after ICH.

Consistency of the Signature of Phonotraumatic Vocal Hyperfunction Across Different Ambulatory Voice Measures.

Journal of speech, language, and hearing research : JSLHR
PURPOSE: Although different factors and voice measures have been associated with phonotraumatic vocal hyperfunction (PVH), it is unclear what percentage of individuals with PVH exhibit such differences during their daily lives. This study used a mach...

SEP-AlgPro: An efficient allergen prediction tool utilizing traditional machine learning and deep learning techniques with protein language model features.

International journal of biological macromolecules
Allergy is a hypersensitive condition in which individuals develop objective symptoms when exposed to harmless substances at a dose that would cause no harm to a "normal" person. Most current computational methods for allergen identification rely on ...

Comparative analysis of machine learning methods for prediction of chlorophyll-a in a river with different hydrology characteristics: A case study in Fuchun River, China.

Journal of environmental management
Eutrophication is a serious threat to water quality and human health, and chlorophyll-a (Chla) is a key indicator to represent eutrophication in rivers or lakes. Understanding the spatial-temporal distribution of Chla and its accurate prediction are ...

Exome sequence analysis identifies rare coding variants associated with a machine learning-based marker for coronary artery disease.

Nature genetics
Coronary artery disease (CAD) exists on a spectrum of disease represented by a combination of risk factors and pathogenic processes. An in silico score for CAD built using machine learning and clinical data in electronic health records captures disea...

Unraveling the multiple chronic conditions patterns among people with Alzheimer's disease and related dementia: A machine learning approach to incorporate synergistic interactions.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Most people with Alzheimer's disease and related dementia (ADRD) also suffer from two or more chronic conditions, known as multiple chronic conditions (MCC). While many studies have investigated the MCC patterns, few studies have consid...