AIMC Topic: Machine Learning

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A novel hybrid model based on two-stage data processing and machine learning for forecasting chlorophyll-a concentration in reservoirs.

Environmental science and pollution research international
The accurate and efficient prediction of chlorophyll-a (Chl-a) concentration is crucial for the early detection of algal blooms in reservoirs. Nevertheless, predicting Chl-a concentration in multivariate time series poses a significant challenge due ...

A hybrid stacked ensemble and Kernel SHAP-based model for intelligent cardiotocography classification and interpretability.

BMC medical informatics and decision making
BACKGROUND: Intelligent cardiotocography (CTG) classification can assist obstetricians in evaluating fetal health. However, high classification performance is often achieved by complex machine learning (ML)-based models, which causes interpretability...

Machine learning-based approaches for ubiquitination site prediction in human proteins.

BMC bioinformatics
Protein ubiquitination is a critical post-translational modification (PTMs) involved in numerous cellular processes. Identifying ubiquitination sites (Ubi-sites) on proteins offers valuable insights into their function and regulatory mechanisms. Due ...

Machine learning models predict PTSD severity and functional impairment: A personalized medicine approach for uncovering complex associations among heterogeneous symptom profiles.

Psychological trauma : theory, research, practice and policy
OBJECTIVE: Posttraumatic stress disorder (PTSD) is a debilitating psychiatric illness, experienced by approximately 10% of the population. Heterogeneous presentations that include heightened dissociation, comorbid anxiety and depression, and emotion ...

Predicting the efficiency of arsenic immobilization in soils by biochar using machine learning.

Journal of environmental sciences (China)
Arsenic (As) pollution in soils is a pervasive environmental issue. Biochar immobilization offers a promising solution for addressing soil As contamination. The efficiency of biochar in immobilizing As in soils primarily hinges on the characteristics...

A Systematic Approach Focused on Machine Learning Models for Exploring the Landscape of Physiological Measurement and Estimation Using Photoplethysmography (PPG).

Journal of cardiovascular translational research
A non-invasive optical technique known as photoplethysmography (PPG) can be used to provide various physiological measurements and estimations. PPG can be used to assess cardiovascular disease (CVD). Hypertension is a primary risk factor for CVD and ...

Construct validation of machine learning for accurately predicting the risk of postoperative surgical site infection following spine surgery.

The Journal of hospital infection
BACKGROUND: This study aimed to evaluate the risk factors for machine learning (ML) algorithms in predicting postoperative surgical site infection (SSI) following spine surgery.

Recent Advances and Challenges in Enzymatic Depolymerization and Recycling of PET Wastes.

Chembiochem : a European journal of chemical biology
Poly (ethylene terephthalate) (PET) is one of the most commonly used plastics in daily life and various industries. Enzymatic depolymerization and recycling of post-consumer PET (pc-PET) provides a promising strategy for the sustainable circular econ...

Machine Learning Facial Emotion Classifiers in Psychotherapy Research: A Proof-of-Concept Study.

Psychopathology
BACKGROUND: New advances in the field of machine learning make it possible to track facial emotional expression with high resolution, including micro-expressions. These advances have promising applications for psychotherapy research, since manual cod...

Novel research and future prospects of artificial intelligence in cancer diagnosis and treatment.

Journal of hematology & oncology
Research into the potential benefits of artificial intelligence for comprehending the intricate biology of cancer has grown as a result of the widespread use of deep learning and machine learning in the healthcare sector and the availability of highl...