AIMC Topic: Machine Learning

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Artificial intelligence in orthopedics: fundamentals, current applications, and future perspectives.

Military Medical Research
Conventional diagnostic and therapeutic approaches in orthopedics are frequently time intensive and associated with elevated rates of diagnostic error, underscoring the urgent need for more efficient tools to improve the current situation. Recently, ...

NAFLD progression in metabolic syndrome: a Raman spectroscopy and machine learning approach in an animal model.

The Analyst
Nonalcoholic fatty liver disease (NAFLD) is emerging as the leading cause of chronic liver disease in many regions, particularly in association with the rising prevalence of Metabolic syndrome (MetS), affecting more than 30% of the population worldwi...

Exhaled gas biomarkers: a non-invasive approach for distinguishing diabetes and its complications.

The Analyst
Exhaled gas detection offers a safe, convenient, and non-invasive clinical diagnostic method for preventing the progression of diabetes to complications. In this study, gas chromatography-mass spectrometry (GC-MS) analysis and statistical methods wer...

Machine learning and SHAP value interpretation for predicting the response to neoadjuvant chemotherapy and long-term clinical outcomes in Chinese female breast cancer.

Annals of medicine
BACKGROUND: Most models of neoadjuvant chemotherapy (NACT) for breast cancer (BC) suffer from insufficient data and lack interpretability. Additionally, there is a notable absence of reports from China in this field. This study is also the first to i...

Sentiment analysis for deepfake X posts using novel transfer learning based word embedding and hybrid LGR approach.

Scientific reports
With the growth of social media, people are sharing more content than ever, including X posts that reflect a variety of emotions and opinions. AI-generated synthetic text, known as deepfake text, is used to imitate human writing to disseminate mislea...

Cross-subject EEG signals-based emotion recognition using contrastive learning.

Scientific reports
Electroencephalography (EEG) signals based emotion brain computer interface (BCI) is a significant field in the domain of affective computing where EEG signals are the cause of reliable and objective applications. Despite these advancements, signific...

The Predictive Value of Serum Total IgE for Antihistamine Treatment Outcomes in Chinese Patients with Chronic Spontaneous Urticaria.

Acta dermato-venereologica
Chronic spontaneous urticaria is a common skin disorder with variable treatment responses. Second-generation H1-antihistamines are the first-line treatment for chronic spontaneous urticaria, yet many patients fail to respond to licensed doses. Predic...

Interpretable bioinformatics approaches for pheochromocytoma bioactivity and protein interaction analysis.

Computers in biology and medicine
Pheochromocytoma (PCC) is a rare neuroendocrine tumor driven by complex molecular mechanisms, notably involving the oncogenic c-Myc/Max and c-Myc/c-Max protein complexes. Despite their pivotal role in tumor progression, the molecular interactions and...

Multi-omics analysis of plasma and CSF in spontaneous diabetic cynomolgus monkeys: Unravelling and validating the key molecular markers that predict the preclinical pathological formation of Alzheimer's disease.

Computers in biology and medicine
Alzheimer's disease (AD) biomarkers (Aβ42 or Tau 181) have high diagnostic performance. However, when they are altered, it indicates that irreversible pathology has developed in the brain. Therefore, there is a lack of early prediction or monitoring ...

Age-related variation in hemoglobin glycation index and stroke mortality: mediation and machine learning in a cohort study.

Scientific reports
To investigate the associations between both age and the hemoglobin glycation index (HGI) and the 30-day and 1-year mortality in ischemic stroke (IS) patients and to analyze the mediating effect of the HGI on the relationship between age and mortalit...