AIMC Topic: Machine Learning

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Modelling of pome fruit pollen performance using machine learning.

Scientific reports
Agriculture, particularly fruit production, is considered a crucial industry with a significant economic impact in many countries. Extreme fluctuations in air temperature can negatively affect the flowering periods of fruit species. Therefore, it is ...

Early detection of feline chronic kidney disease via 3-hydroxykynurenine and machine learning.

Scientific reports
Feline chronic kidney disease (CKD) is one of the most frequently encountered diseases in veterinary practice, and the leading cause of mortality in cats over five years of age. While diagnosing advanced CKD is straightforward, current routine tests ...

Estimation of Machine Learning-Based Models to Predict Dementia Risk in Patients With Atherosclerotic Cardiovascular Diseases: UK Biobank Study.

JMIR aging
BACKGROUND: The atherosclerotic cardiovascular disease (ASCVD) is associated with dementia. However, the risk factors of dementia in patients with ASCVD remain unclear, necessitating the development of accurate prediction models.

Complete Blood Count and Monocyte Distribution Width-Based Machine Learning Algorithms for Sepsis Detection: Multicentric Development and External Validation Study.

Journal of medical Internet research
BACKGROUND: Sepsis is an organ dysfunction caused by a dysregulated host response to infection. Early detection is fundamental to improving the patient outcome. Laboratory medicine can play a crucial role by providing biomarkers whose alteration can ...

Predicting Agitation-Sedation Levels in Intensive Care Unit Patients: Development of an Ensemble Model.

JMIR medical informatics
BACKGROUND: Agitation and sedation management is critical in intensive care as it affects patient safety. Traditional nursing assessments suffer from low frequency and subjectivity. Automating these assessments can boost intensive care unit (ICU) eff...

Multi-omics analyses and machine learning prediction of oviductal responses in the presence of gametes and embryos.

eLife
The oviduct is the site of fertilization and preimplantation embryo development in mammals. Evidence suggests that gametes alter oviductal gene expression. To delineate the adaptive interactions between the oviduct and gamete/embryo, we performed a m...

Machine learning-based optimal design of fibrillar adhesives.

Journal of the Royal Society, Interface
Fibrillar adhesion, observed in animals like beetles, spiders and geckos, relies on nanoscopic or microscopic fibrils to enhance surface adhesion via 'contact splitting'. This concept has inspired engineering applications across robotics, transportat...

Development of a tertiary lymphoid structure-based prognostic model for breast cancer: integrating single-cell sequencing and machine learning to enhance patient outcomes.

Frontiers in immunology
BACKGROUND: Breast cancer, a highly prevalent global cancer, poses significant challenges, especially in advanced stages. Prognostic models are crucial to enhance patient outcomes. Tertiary lymphoid structures (TLS) within the tumor microenvironment ...

Leveraging diverse cell-death patterns in diagnosis of sepsis by integrating bioinformatics and machine learning.

PeerJ
BACKGROUND: Sepsis is a life-threatening disease causing millions of deaths every year. It has been reported that programmed cell death (PCD) plays a critical role in the development and progression of sepsis, which has the potential to be a diagnosi...