AIMC Topic: Machine Learning

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Application of CO Supercritical Fluid to Optimize the Solubility of Oxaprozin: Development of Novel Machine Learning Predictive Models.

Molecules (Basel, Switzerland)
Over the last years, extensive motivation has emerged towards the application of supercritical carbon dioxide (SCCO) for particle engineering. SCCO has great potential for application as a green and eco-friendly technique to reach small crystalline p...

Comparing machine learning algorithms to predict 5-year survival in patients with chronic myeloid leukemia.

BMC medical informatics and decision making
INTRODUCTION: Chronic myeloid leukemia (CML) is a myeloproliferative disorder resulting from the translocation of chromosomes 19 and 22. CML includes 15-20% of all cases of leukemia. Although bone marrow transplant and, more recently, tyrosine kinase...

Alternative stopping rules to limit tree expansion for random forest models.

Scientific reports
Random forests are a popular type of machine learning model, which are relatively robust to overfitting, unlike some other machine learning models, and adequately capture non-linear relationships between an outcome of interest and multiple independen...

Probing the rules of cell coordination in live tissues by interpretable machine learning based on graph neural networks.

PLoS computational biology
Robustness in developing and homeostatic tissues is supported by various types of spatiotemporal cell-to-cell interactions. Although live imaging and cell tracking are powerful in providing direct evidence of cell coordination rules, extracting and c...

Relationship between Liquid-Based Cytology Preservative Solutions and Artificial Intelligence: Liquid-Based Cytology Specimen Cell Detection Using YOLOv5 Deep Convolutional Neural Network.

Acta cytologica
INTRODUCTION: Deep learning is a subset of machine learning that has contributed to significant changes in feature extraction and image classification and is being actively researched and developed in the field of cytopathology. Liquid-based cytology...

Federated machine learning for a facilitated implementation of Artificial Intelligence in healthcare - a proof of concept study for the prediction of coronary artery calcification scores.

Journal of integrative bioinformatics
The implementation of Artificial Intelligence (AI) still faces significant hurdles and one key factor is the access to data. One approach that could support that is federated machine learning (FL) since it allows for privacy preserving data access. F...

Development and validation of a machine-learning algorithm to predict the relevance of scientific articles within the field of teratology.

Reproductive toxicology (Elmsford, N.Y.)
The Dutch Teratology Information Service Lareb counsels healthcare professionals and patients about medication use during pregnancy and lactation. To keep the evidence up to date, employees perform a standardized weekly PubMed query where relevant li...

Is handling unbalanced datasets for machine learning uplifts system performance?: A case of diabetic prediction.

Diabetes & metabolic syndrome
BACKGROUND AND AIMS: Healthcare is a sensitive sector, and addressing the class imbalance in the healthcare domain is a time-consuming task for machine learning-based systems due to the vast amount of data. This study looks into the impact of socioec...

Detection of Malicious Cloud Bandwidth Consumption in Cloud Computing Using Machine Learning Techniques.

Computational intelligence and neuroscience
The Internet of Things, sometimes known as IoT, is a relatively new kind of Internet connectivity that connects physical objects to the Internet in a way that was not possible in the past. The Internet of Things is another name for this concept (IoT)...