AIMC Topic: Machine Learning

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Molecular causality in the advent of foundation models.

Molecular systems biology
Correlation is not causation: this simple and uncontroversial statement has far-reaching implications. Defining and applying causality in biomedical research has posed significant challenges to the scientific community. In this perspective, we attemp...

High Glass Transition Temperature Fluorinated Polymers Based on Transfer Learning with Small Experimental Data.

Macromolecular rapid communications
Machine learning can be used to predict the properties of polymers and explore vast chemical spaces. However, the limited number of available experimental datasets hinders the enhancement of the predictive performance of a model. This study proposes ...

Association of Cardiovascular Health With Brain Age Estimated Using Machine Learning Methods in Middle-Aged and Older Adults.

Neurology
BACKGROUND AND OBJECTIVES: Cardiovascular health (CVH) has been associated with cognitive decline and dementia, but the extent to which CVH affects brain health remains unclear. We investigated the association of CVH, assessed using Life's Essential ...

Identifying Driving Factors of Atmospheric NO with Machine Learning.

Environmental science & technology
Dinitrogen pentoxide (NO) plays an essential role in tropospheric chemistry, serving as a nocturnal reservoir of reactive nitrogen and significantly promoting nitrate formations. However, identifying key environmental drivers of NO formation remains ...

A Paper-Based Multiplexed Serological Test to Monitor Immunity against SARS-COV-2 Using Machine Learning.

ACS nano
The rapid spread of SARS-CoV-2 caused the COVID-19 pandemic and accelerated vaccine development to prevent the spread of the virus and control the disease. Given the sustained high infectivity and evolution of SARS-CoV-2, there is an ongoing interest...

Insights into Parkinson's Disease-Related Freezing of Gait Detection and Prediction Approaches: A Meta Analysis.

Sensors (Basel, Switzerland)
Parkinson's Disease (PD) is a complex neurodegenerative disorder characterized by a spectrum of motor and non-motor symptoms, prominently featuring the freezing of gait (FOG), which significantly impairs patients' quality of life. Despite extensive r...

Classification of Visually Induced Motion Sickness Based on Phase-Locked Value Functional Connectivity Matrix and CNN-LSTM.

Sensors (Basel, Switzerland)
To effectively detect motion sickness induced by virtual reality environments, we developed a classification model specifically designed for visually induced motion sickness, employing a phase-locked value (PLV) functional connectivity matrix and a C...

Noninvasive prediction of lymph node metastasis in pancreatic cancer using an ultrasound-based clinicoradiomics machine learning model.

Biomedical engineering online
OBJECTIVES: This study was designed to explore and validate the value of different machine learning models based on ultrasound image-omics features in the preoperative diagnosis of lymph node metastasis in pancreatic cancer (PC).

An explainable machine learning-based model to predict intensive care unit admission among patients with community-acquired pneumonia and connective tissue disease.

Respiratory research
BACKGROUND: There is no individualized prediction model for intensive care unit (ICU) admission on patients with community-acquired pneumonia (CAP) and connective tissue disease (CTD) so far. In this study, we aimed to establish a machine learning-ba...