AIMC Topic: Machine Learning

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Reliability of noninvasive hyperspectral tongue diagnosis for menstrual diseases using machine learning method.

Scientific reports
The outward appearance of human tongue can reflect changes in blood circulation caused by pathological states, and it has been used as an assisted method for clinical diseases diagnosis for thousands of years in China. The purpose of this study is to...

Remote sensing estimation of aboveground biomass of different forest types in Xinjiang based on machine learning.

Scientific reports
Forest aboveground biomass (AGB) is a key indicator reflecting the function and quality of forest ecosystems, and accurate large-scale estimations of forest AGB are essential for effective forest ecosystem management. However, owing to limitations in...

Predicting hepatocellular carcinoma survival with artificial intelligence.

Scientific reports
Despite the extensive research on hepatocellular carcinoma (HCC) exploring various treatment strategies, the survival outcomes have remained unsatisfactory. The aim of this research was to evaluate the ability of machine learning (ML) methods in pred...

Reinforcement-based leveraging transfer learning for multiclass optical coherence tomography images classification.

Scientific reports
The accurate diagnosis of retinal diseases, such as Diabetic Macular Edema (DME) and Age-related Macular Degeneration (AMD), is essential for preventing vision loss. Optical Coherence Tomography (OCT) imaging plays a crucial role in identifying these...

Explainable artificial intelligence of DNA methylation-based brain tumor diagnostics.

Nature communications
We have recently developed a machine learning classifier that enables fast, accurate, and affordable classification of brain tumors based on genome-wide DNA methylation profiles that is widely employed in the clinic. Neuro-oncology research would ben...

Predicting the Risk of HIV Infection and Sexually Transmitted Diseases Among Men Who Have Sex With Men: Cross-Sectional Study Using Multiple Machine Learning Approaches.

Journal of medical Internet research
BACKGROUND: Men who have sex with men (MSM) are at high risk for HIV infection and sexually transmitted diseases (STDs). However, there is a lack of accurate and convenient tools to assess this risk.

Artificial intelligence algorithm for preoperative prediction of FIGO stage in ovarian cancer based on clinical features integrated 18F-FDG PET/CT metabolic and radiomics features.

Journal of cancer research and clinical oncology
PURPOSE: The International Federation of Gynecology and Obstetric (FIGO) stage is critical to guiding the treatments of ovarian cancer (OC). We tried to develop a model to predict the FIGO stage of OC through machine learning algorithms with patients...

Proteomic associations with cognitive variability as measured by the Wisconsin Card Sorting Test in a healthy Thai population: A machine learning approach.

PloS one
Inter-individual cognitive variability, influenced by genetic and environmental factors, is crucial for understanding typical cognition and identifying early cognitive disorders. This study investigated the association between serum protein expressio...

The mind-machine connection: adaptive information processing and new technologies promoting mental health in older adults.

The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry
The human brain demonstrates an exceptional adaptability, which encompasses the ability to regulate emotions, exhibit cognitive flexibility, and generate behavioral responses, all supported by neuroplasticity. Brain-computer interfaces (BCIs) employ ...

Identification of a novel hypermethylation marker, ZSCAN18, and construction of a diagnostic model in cervical cancer.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
PURPOSE: Cervical cancer (CC), a common female malignancy, has been linked to alterations in DNA methylation. This study employed an integrated "dry-wet lab" strategy combining bioinformatics, machine learning, and experimental validation to identify...