AIMC Topic: Machine Learning

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CalTrig: A GUI-Based Machine Learning Approach for Decoding Neuronal Calcium Transients in Freely Moving Rodents.

eNeuro
Advances in in vivo Ca imaging using miniature microscopes have enabled researchers to study single-neuron activity in freely moving animals. Tools such as Minian and CalmAn have been developed to convert Ca visual signals to numerical data, collecti...

Applying binary mixed model to predict knee osteoarthritis pain.

PloS one
Data used to understand knee osteoarthritis (KOA) often involves knee-level, rather than person-level information. Failure to account for the correlation between joints within a person may lead to inaccurate inferences. The aim of this study was to d...

Driven early detection of chronic kidney cancer disease based on machine learning technique.

PloS one
In recent times, chronic kidney cancer has been considered a significant cause of cancer, and Renal Cell Carcinoma (RCC) has become a significant prevalent among various kidney cancer conditions. The analysis of kidney cancer, an important and often ...

Exploration of the fluorine-fluorine interaction mechanism in fluoroquinolone antibiotics recognition and ciprofloxacin detection on the basis of fluorine-doped carbon quantum dots and machine learning.

Food chemistry
The uncontrolled use of antibiotics poses a significant threat to human health and ecosystems. Accurate differentiation and trace detection of fluoroquinolone antibiotics (FQs) in foods are imperative. Fluorine-doped carbon quantum dots chelated with...

Unraveling long-term health dynamics of impounded lakes integrating water diversion-adapted planktonic index of biotic integrity and machine learning.

Environmental research
Assessing ecosystem integrity of impounded lakes subjected to sustained water diversion is fundamental for advancing adaptive water governance. Nevertheless, drivers of lake health variation under recurrent flow regulation, particularly their multisc...

[Construction of interpretable predictive model of acupuncture for methadone reduction in patients undergoing methadone maintenance treatment based on machine learning and SHAP].

Zhongguo zhen jiu = Chinese acupuncture & moxibustion
OBJECTIVE: To construct a predictive model for the reduction in methadone maintenance treatment (MMT) and evaluate the effects of different interventions and other clinical factors on methadone reduction using Shapley additive explanations (SHAP).

Identification of necroptotic biomarkers associated with immune microenvironment in sepsis based on the protein-protein interaction network and machine learning.

Clinica chimica acta; international journal of clinical chemistry
BACKGROUND: Necroptosis is inflammatorily sparked and closely associated with sepsis, but the crosstalk between necroptosis and inflammation in sepsis has rarely been studied in depth. This study is designed to reveal the role of necroptosis in the p...

ML-based prediction to experimental validation: Development of dihydroquinazoline based multi-potent ligands as anti-Alzheimer's agents.

Computers in biology and medicine
Alzheimer's disease (AD) is a multifactorial neurological disorder accounting for the cognitive decline in the patients. The disease is linked to numerous pathological factors including hyperactivation of acetylcholinesterase (AChE) and monoamine oxi...

Synergizing Nanosensor-Enhanced Wearable Devices with Machine Learning for Precision Health Management Benefiting Older Adult Populations.

ACS nano
Population aging presents significant health challenges and socioeconomic burdens globally, driving an increased demand for precision health management. In the era of big data, the exponential growth of health information is accelerating advances in ...

Predicting the Site-Specific Toxicity of Metals to Fishes Using a New Machine Learning-Based Approach.

Environmental science & technology
Fishes of various trophic levels play an important role in the stability and balance of aquatic ecosystems. Metal contaminants can impair the survival and population fitness of fish at elevated concentrations. When universal water quality criteria (W...