AIMC Topic: Machine Learning

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Multi-omics driven computational framework for cancer molecular subtype classification.

Scientific reports
Cancer molecular subtype classification is an essential component of precision oncology which provides insights into cancer prognosis and guides targeted therapy. Despite the growing applications of AI for cancer molecular subtype classification, cha...

Functional dynamics between resident transcriptionally active microbes (TAMs) and host genes underlie Dengue severity.

PLoS neglected tropical diseases
Host-microbe interactions are increasingly recognized as an important module to understand disease progression and potential treatment strategies. Increasing evidence points to the microbiome's ability to modulate host gene expression, and thereby in...

Machine learning-based risk prediction model for cognitive dysfunction in elderly individuals.

PloS one
BACKGROUND: With the advancement of globalization, the prevalence of cognitive dysfunction in the elderly population has risen significantly. Early intervention may dramatically alleviate the disease burden and reduce economic costs associated with c...

A novel prognostic model for lung squamous cell carcinoma based on multi-omics analysis and machine learning.

PloS one
Lung squamous-cell carcinoma (LUSC) is a highly aggressive malignancy with a poor prognosis. Tertiary lymphoid structures (TLS) play a crucial role in the immune response and significantly influence the efficacy of immunotherapy. However, the prognos...

Predicting the influence of homologous recombination repair deficiency genes on glioma heterogeneity and patient prognosis using multi-omics analysis and machine learning.

PloS one
BACKGROUND: Glioma is the most common malignant tumor of the central nervous system, and homologous recombination deficiency (HRD) may play a crucial role in its progression. Our study aimed to predict the impact of HRD on glioma heterogeneity and pa...

Leading predictors and their associations with combination opioid pain therapy in older adults with cancer: Application of machine learning approaches.

PloS one
Combined use of opioids and other pharmacological therapies used for pain management, such as non-steroidal anti-inflammatory drugs (NSAIDs), benzodiazepines, gabapentinoids, and/or skeletal muscle relaxants (SMRs), in older adult cancer survivors ca...

Dual niche modeling with GEE and SHAP for predicting habitat shifts of Haloxylon ammodendron and Cistanche deserticola under climate change.

PloS one
Haloxylon ammodendron, a keystone woody species, and its parasitic plant, Cistanche deserticola, play critical roles in sustaining arid ecosystems and supporting regional economies. However, their distribution is increasingly threatened by global cli...

Using machine learning techniques for predicting the dropout of undergraduate students in Brazilian courses of statistics.

Anais da Academia Brasileira de Ciencias
This research aims to propose a machine learning approach to classify dropout outcomes among students in Statistics undergraduate programs in Brazil, identifying the most important factors associated with this phenomenon. This study uses microdata fr...

Research on the detection of foreign materials in tobacco shreds based on hyperspectral reflection imaging technology combined with machine learning.

Scientific reports
Plastic and paper foreign materials in tobacco shreds mainly originate from tobacco processing and packaging. These materials are highly similar to tobacco shreds in color and size, making them difficult for traditional machine vision systems to dete...

Comparison of machine learning classification and regression models for prediction of academic performance among postgraduate public health students.

Scientific reports
Machine learning (ML) is an artificial intelligence tool that focuses on learning by generating models using established algorithms that represent a given dataset. It can be used as a predictive tool for students' academic performance (AP) at both un...