AIMC Topic: Machine Learning

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Applications of Machine Learning in Periodontology and Implantology: A Comprehensive Review.

Annals of biomedical engineering
Machine learning (ML) has led to significant advances in dentistry, easing the workload of professionals and improving the performance of various medical processes. The fields of periodontology and implantology can profit from these advances for task...

Identification of Bloodstains by Species Using Extreme Learning Machine and Hyperspectral Imaging Technology.

Applied spectroscopy
How to identify bloodstains and obtain some potential evidence is of great significance for solving criminal cases. First, the spectral data of different species of bloodstain samples (human blood and animal blood) were acquired by using a hyperspect...

Prediction of g-CN-based photocatalysts in tetracycline degradation based on machine learning.

Chemosphere
Investigating the effects of g-CN-based photocatalysts on experimental parameters during tetracycline (TC) degradation can be helpful in discovering the optimal parameter combinations to improve the degradation efficiencies in general. Machine learni...

Uncovering the most robust predictors of problematic pornography use: A large-scale machine learning study across 16 countries.

Journal of psychopathology and clinical science
Problematic pornography use (PPU) is the most common manifestation of the newly introduced compulsive sexual behavior disorder diagnosis in the 11th revision of the International Classification of Diseases. Research related to PPU has proliferated in...

Prediction of post-delivery hemoglobin levels with machine learning algorithms.

Scientific reports
Predicting postpartum hemorrhage (PPH) before delivery is crucial for enhancing patient outcomes, enabling timely transfer and implementation of prophylactic therapies. We attempted to utilize machine learning (ML) using basic pre-labor clinical data...

A novel blood-based epigenetic biosignature in first-episode schizophrenia patients through automated machine learning.

Translational psychiatry
Schizophrenia (SCZ) is a chronic, severe, and complex psychiatric disorder that affects all aspects of personal functioning. While SCZ has a very strong biological component, there are still no objective diagnostic tests. Lately, special attention ha...

Study of machine learning techniques for outcome assessment of leptospirosis patients.

Scientific reports
Leptospirosis is a global disease that impacts people worldwide, particularly in humid and tropical regions, and is associated with significant socio-economic deficiencies. Its symptoms are often confused with other syndromes, which can compromise cl...

A supramolecular fluorescence sensor array for the differentiation of multiple anions and prediction of iodine in artificial urine using machine learning.

Mikrochimica acta
The simultaneous discrimination and detection of multiple anions in an aqueous solution has been a major challenge due to their structural similarity and low charge radii. In this study, we have constructed a supramolecular fluorescence sensor array ...

Enhancing drought resilience: machine learning-based vulnerability assessment in Uttar Pradesh, India.

Environmental science and pollution research international
Drought is a natural and complex climatic hazard. It has both natural and social connotations. The purpose of this study is to use machine learning methods (MLAs) for drought vulnerability (DVM) in Uttar Pradesh, India. There were 18 factors used to ...

Missing data in amortized simulation-based neural posterior estimation.

PLoS computational biology
Amortized simulation-based neural posterior estimation provides a novel machine learning based approach for solving parameter estimation problems. It has been shown to be computationally efficient and able to handle complex models and data sets. Yet,...