AIMC Topic: Machine Learning

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Multi-marker discovery for mild cognitive impairment in metabolomics using machine learning with a global surrogate model via partial least squares.

Metabolomics : Official journal of the Metabolomic Society
INTRODUCTION: Dementia can be prevented through early intervention; hence, there is an urgent need for biomarkers to help diagnose mild cognitive impairment (MCI).

Machine learning-based groundwater potential mapping and factor analysis in tropical lateritic terrains using self-organizing maps and random forest.

Environmental monitoring and assessment
Groundwater potential mapping is essential for sustainable water resource management, particularly in tropical lateritic terrains where communities depend heavily on groundwater for domestic and agricultural needs. This study delineates groundwater p...

Nanosensor-Based Pattern-Generating Probe Accelerates Sepsis Diagnosis.

ACS nano
Biomimetic optical sensor arrays hold promising potential in differentiating nuances within intricate mixtures and biosamples. Nonetheless, developing a standalone pattern-generating sensor for multianalyte identification in clinical biofluids, witho...

Machine learning-based screening and validation of pyroptosis-associated prognostic genes and potential drugs in cervical cancer.

BMC medical genomics
Pyroptosis is a newly discovered form of programmed cell death, but its mechanism in the development of cervical cancer has not been elucidated. Cervical cancer differentially expressed pyroptosis-related genes were identified via bioinformatic analy...

Development of a consensus molecular classifier for pancreatic ductal adenocarcinoma.

Genome medicine
BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) presents a significant challenge, with a 5-year survival rate of approximately 10%. Tumor heterogeneity contributes to the limited effectiveness of treatments. Several tumor and stroma molecular cla...

Artificial intelligence-driven kidney organ allocation: systematic review of clinical outcome prediction, ethical frameworks, and decision-making algorithms.

BMC nephrology
Kidney transplantation remains the optimal treatment for end-stage renal disease, yet persistent organ shortages and inequitable allocation necessitate innovative solutions. Artificial intelligence (AI) and machine learning (ML) have emerged as promi...

Prediction of uterine cavity conception environment using two-dimensional transvaginal ultrasound imaging semantic feature-based machine learning: a case-control study.

BMC pregnancy and childbirth
BACKGROUND: Independently investigating the association between pregnancy outcomes and the uterine cavity conception environment (UCCE) is challenging. Therefore, this study aimed to employ a range of machine learning algorithms to systematically ana...

Quantum machine learning driven optimization of nutrient-hormone interactions for enhanced in vitro regeneration of common bean.

BMC plant biology
Common bean (Phaseoulus vulgarsis) is an important edible legume crop, but its improvement through modern biotechnological tools has been limited due to the lack of efficient and reproducible in vitro regeneration protocols. This bottleneck restricts...

Explainable machine learning for predicting clinical outcomes in HIV/TB co-infection: a comparative retrospective study.

BMC infectious diseases
BACKGROUND: HIV/TB co-infection presents substantial public-health challenges, showing greater treatment-failure and mortality rates than tuberculosis alone. Recent advances in machine learning (ML) provide a robust means of identifying high-risk pat...