AIMC Topic: Machine Learning

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Recognizing Skateboard and Kickboard Commuting Behaviors Using Activity Trackers: Feasibility Study Using Machine Learning Approaches.

JMIR formative research
BACKGROUND: Active commuting, such as skateboarding and kickboarding, is gaining popularity as an alternative to traditional modes of transportation such as walking and cycling. However, current activity trackers and smartphones, which rely on accele...

Label-free diagnostic procedure for hirschsprung's disease to detect intestinal mucosal characteristics of aganglionosis by Raman spectroscopy with optimized decision algorithms.

Lasers in medical science
PURPOSE: Hirschsprung's disease (HSCR) is an intestinal disorder characterized by the absence of nerve cells in parts of the intestinal tract. The definitive diagnosis is confirmed by a full-thickness rectal biopsy to verify the absence of ganglion c...

Prediction-powered inference for clinical trials: application to linear covariate adjustment.

BMC medical research methodology
Prediction-powered inference (PPI) (Angelopoulos et al., Science 382(6671):669-674, 2023) and its subsequent development called PPI++ (Angelopoulos et al., 2023) provide a novel approach to standard statistical estimation, leveraging machine learning...

SamRobNODDI:-space sampling-augmented continuous representation learning for robust and generalized NODDI.

Physics in medicine and biology
. Neurite orientation dispersion and density imaging (NODDI) microstructure estimation from diffusion magnetic resonance imaging (dMRI) is of great significance for the discovery and treatment of various neurological diseases. Current deep learning-b...

Arab2Vec: An Arabic word embedding model for use in Twitter NLP applications.

PloS one
The analysis of Arabic Twitter data sets is a highly active research topic, particularly since the outbreak of COVID-19 and subsequent attempts to understand public sentiment related to the pandemic. This activity is partially driven by the high numb...

Predicting one-year post-surgical recurrence in colorectal liver metastasis using CT radiomics and machine learning.

PloS one
BACKGROUND: Early recurrence in colorectal cancer liver metastases (CRLM) typically correlates with significantly worse survival outcomes. There is a strong demand for developing robust and interpretable approaches to assist clinicians in identifying...

MACML: Marrying attention and convolution-based meta-learning method for few-shot IoT intrusion detection.

PloS one
The widespread deployment of Internet of Things (IoT) devices has made them prime targets for cyberattacks. Existing intrusion detection systems (IDSs) heavily rely on large-scale labeled datasets, which limits their effectiveness in detecting novel ...

Neural correlates of metacognition in education: a machine learning approach.

Neuropsychologia
Metacognition, the ability to reflect and regulate one's cognitive processes, has been shown to play a role in various aspects of life, particularly in academic settings. While important steps have been made in uncovering the neural basis of metacogn...

Integrated single-cell and clinical transcriptomic analysis identifies blunted glycolytic activation as a hallmark of maladaptive repair in renal ischemia-reperfusion.

Renal failure
Acute kidney injury (AKI) is a common and increases risk of chronic kidney disease (CKD). While mitochondrial dysfunction drives maladaptive repair, the role of glycolysis in renal recovery remains unclear. Here, we integrated single-cell transcripto...

Adipocyte-selective mRNA lipid nanoparticles for cell programming with machine learning analysis.

Journal of controlled release : official journal of the Controlled Release Society
Adipose tissue plays a crucial role in energy metabolism and endocrine signaling. White adipose tissue (WAT), in particular, is a compelling target for therapeutic interventions in metabolic diseases due to its secretory capacity and abundance. Gene ...