AIMC Topic: Machine Learning

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Leveraging textual information for social media news categorization and sentiment analysis.

PloS one
The rise of social media has changed how people view connections. Machine Learning (ML)-based sentiment analysis and news categorization help understand emotions and access news. However, most studies focus on complex models requiring heavy resources...

GMAC-A Simple Measure to Quantify Upper Limb Use From Wrist-Worn Accelerometers.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Various measures have been proposed to quantify upper-limb use through wrist-worn inertial measurement units. The two most popular traditional measures of upper-limb use - thresholded activity counts (TAC) and the gross movement (GM) score suffer fro...

Near infrared spectroscopy (NIRS) and machine learning as a promising tandem for fast viral detection in serum microsamples: A preclinical proof of concept.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Fast detection of viral infections is a key factor in the strategy for the prevention of epidemics expansion and follow-up. Hepatitis C is paradigmatic within viral infectious diseases and major challenges to elimination still remain. Near infrared s...

Predicting the 28-day prognosis of acute-on-chronic liver failure patients based on machine learning.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
BACKGROUND: We aimed to establish a prognostic predictive model based on machine learning (ML) methods to predict the 28-day mortality of acute-on-chronic liver failure (ACLF) patients, and to evaluate treatment effectiveness.

Uncovering substrate specificity determinants of class IIb aminoacyl-tRNA synthetases with machine learning.

Journal of molecular graphics & modelling
Specific amino acid (AA) binding by aminoacyl-tRNA synthetases (aaRSs) is necessary for correct translation of the genetic code. Sequence and structure analyses have revealed the main specificity determinants and allowed a partitioning of aaRSs into ...

Quantum-level machine learning calculations of Levodopa.

Computational biology and chemistry
Many drug molecules contain functional groups, resulting in a torsional barrier corresponding to rotation around the bond linking the fragments. In medicinal chemistry and pharmaceutical sciences, inclusive of drug design studies, the exact calculati...

Speech-based recognition and estimating severity of PTSD using machine learning.

Journal of affective disorders
BACKGROUND: Traditional methodologies for diagnosing post-traumatic stress disorder (PTSD) primarily rely on interviews, incurring considerable costs and lacking objective indices. Integrating biomarkers and machine learning techniques into this diag...

Comparing human evaluations of eyewitness statements to a machine learning classifier under pristine and suboptimal lineup administration procedures.

Cognition
Recent work highlights the ability of verbal machine learning classifiers to distinguish between accurate and inaccurate recognition memory decisions (Dobbins, 2022; Dobbins & Kantner, 2019; Seale-Carlisle, Grabman, & Dodson, 2022). Given the surge o...

Probing nitro(so) and chloro byproducts and their precursors in natural organic matter during UV/NHCl treatment by FT-ICR MS with machine learning insights.

Water research
The UV/monochloramine (UV/NHCl) process, while efficiently eliminating micropollutants, produces toxic byproducts. This study utilized Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) to investigate molecular-level changes in n...

Hybrid modeling of T-shaped partial least squares regression and transfer learning for formulation and manufacturing process development of new drug products.

International journal of pharmaceutics
T-shaped partial least squares regression (T-PLSR) is a valuable machine learning technique for the formulation and manufacturing process development of new drug products. An accurate T-PLSR model requires experimental data with multiple formulations...