AIMC Topic: Machine Learning

Clear Filters Showing 18821 to 18830 of 34417 articles

Machine learning prediction of sleep stages in dairy cows from heart rate and muscle activity measures.

Scientific reports
Sleep is important for cow health and shows promise as a tool for assessing welfare, but methods to accurately distinguish between important sleep stages are difficult and impractical to use with cattle in typical farm environments. The objective of ...

Health improvement framework for actionable treatment planning using a surrogate Bayesian model.

Nature communications
Clinical decision-making regarding treatments based on personal characteristics leads to effective health improvements. Machine learning (ML) has been the primary concern of diagnosis support according to comprehensive patient information. A prominen...

Smart Portable Pen for Continuous Monitoring of Anaesthetics in Human Serum With Machine Learning.

IEEE transactions on biomedical circuits and systems
Continuous monitoring of anaesthetics infusion is demanded by anaesthesiologists to help in defining personalized dose, hence reducing risks and side effects. We propose the first piece of technology tailored explicitly to close the loop between anae...

Hybrid LSTM Self-Attention Mechanism Model for Forecasting the Reform of Scientific Research in Morocco.

Computational intelligence and neuroscience
Education is the cultivation of people to promote and guarantee the development of society. Education reforms can play a vital role in the development of a country. However, it is crucial to continually monitor the educational model's performance by ...

Leveraging electronic health record data to inform hospital resource management : A systematic data mining approach.

Health care management science
Early identification of resource needs is instrumental in promoting efficient hospital resource management. Hospital information systems, and electronic health records (EHR) in particular, collect valuable demographic and clinical patient data from t...

Clinical risk prediction models and informative cluster size: Assessing the performance of a suicide risk prediction algorithm.

Biometrical journal. Biometrische Zeitschrift
Clinical visit data are clustered within people, which complicates prediction modeling. Cluster size is often informative because people receiving more care are less healthy and at higher risk of poor outcomes. We used data from seven health systems ...

Profiling of contemporary beer styles using liquid chromatography quadrupole time-of-flight mass spectrometry, multivariate analysis, and machine learning techniques.

Analytica chimica acta
Although all beer is brewed using the same four classes of ingredients, contemporary beer styles show wide variation in flavor and color, suggesting differences in their chemical profiles. A selection of 32 beers covering five styles (India pale ale,...

Conditional generation of medical images via disentangled adversarial inference.

Medical image analysis
Synthetic medical image generation has a huge potential for improving healthcare through many applications, from data augmentation for training machine learning systems to preserving patient privacy. Conditional Adversarial Generative Networks (cGANs...

Predictive Approaches for Acute Dialysis Requirement and Death in COVID-19.

Clinical journal of the American Society of Nephrology : CJASN
BACKGROUND AND OBJECTIVES: AKI treated with dialysis initiation is a common complication of coronavirus disease 2019 (COVID-19) among hospitalized patients. However, dialysis supplies and personnel are often limited.

Machine learning for predicting preoperative red blood cell demand.

Transfusion medicine (Oxford, England)
BACKGROUND: The paucity of accurate quantitative standards for determining the quantity of red blood cells (RBCs) needed for perioperative patients and the predominant application of the "preoperative hemoglobin + surgery type" empirical decision-mak...