AIMC Topic: Machine Learning

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Expression of Salivary miRNAs, Clinical, and Demographic Features in the Early Detection of Gastric Cancer: A Statistical and Machine Learning Analysis.

Journal of gastrointestinal cancer
OBJECTIVE: Gastric cancer ranks as one of the top five deadliest cancers worldwide and is often diagnosed at late stages. Analysis of saliva may provide a non-invasive approach for detection of malignancies in organs associated with the oral cavity. ...

QuadTPat: Quadruple Transition Pattern-based explainable feature engineering model for stress detection using EEG signals.

Scientific reports
The most cost-effective data collection method is electroencephalography (EEG), which obtains meaningful information about the brain. Therefore, EEG signal processing is crucial for neuroscience and machine learning (ML). Therefore, a new EEG stress ...

Rapid Raman spectroscopy analysis assisted with machine learning: a case study on Radix Bupleuri.

Journal of the science of food and agriculture
BACKGROUND: Radix Bupleuri has been widely used for its plentiful pharmacological effects. But it is hard to evaluate their safety and efficacy because the concentrations of components are tightly affected by the surrounding environment. Thus, Radix ...

Machine learning for improved medical device management: A focus on defibrillator performance.

Technology and health care : official journal of the European Society for Engineering and Medicine
BackgroundPoorly regulated and insufficiently maintained medical devices (MDs) carry high risk on safety and performance parameters impacting the clinical effectiveness and efficiency of patient diagnosis and treatment. After the MD directive (MDD) h...

Machine learning-based rational design for efficient discovery of allatostatin analogs as promising lead candidates for novel IGRs.

Pest management science
BACKGROUND: Insect neuropeptide allatostatins (ASTs) play a vital role in regulating insect growth, development, and reproduction, making them potential candidates for new insect growth regulators (IGRs). However, the practical use of natural ASTs in...

Machine Learning Approaches for the Fusion of Near-Infrared, Mid-Infrared, and Raman Data to Identify Cartilage Degradation in Human Osteochondral Plugs.

Applied spectroscopy
Vibrational spectroscopy methods such as mid-infrared (MIR), near-infrared (NIR), and Raman spectroscopies have been shown to have great potential for in vivo biomedical applications, such as arthroscopic evaluation of joint injuries and degeneration...

Comparison of machine learning algorithms for automatic prediction of Alzheimer disease.

Journal of the Chinese Medical Association : JCMA
BACKGROUND: Alzheimer disease is a progressive neurological disorder marked by irreversible memory loss and cognitive decline. Traditional diagnostic tools, such as intracranial volume assessments, electroencephalography (EEG) signals, and brain magn...

Milk adulteration identification using hyperspectral imaging and machine learning.

Journal of dairy science
Milk adulteration poses a global concern, with developing countries facing higher risks due to unsatisfactory monitoring systems and policies. Surprisingly, this common issue has often been overlooked in many countries. Contrary to popular belief, ad...

Interpretable causal machine learning optimization tool for improving efficiency of internal carbon source-biological denitrification.

Bioresource technology
Interpretable causal machine learning (ICML) was used to predict the performance of denitrification and clarify the relationships between influencing factors and denitrification. Multiple models were examined, and XG-Boost model provided the best pre...

Predicting frailty in older patients with chronic pain using explainable machine learning: A cross-sectional study.

Geriatric nursing (New York, N.Y.)
Frailty is common among older adults with chronic pain, and early identification is crucial in preventing adverse outcomes like falls, disability, and dementia. However, effective tools for identifying frailty in this population remain limited. This ...