AI Medical Compendium Topic:
Forecasting

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Predicting the serum digoxin concentrations of infants in the neonatal intensive care unit through an artificial neural network.

BMC pediatrics
BACKGROUND: Given its narrow therapeutic range, digoxin's pharmacokinetic parameters in infants are difficult to predict due to variation in birth weight and gestational age, especially for critically ill newborns. There is limited evidence to suppor...

Incorporating medical code descriptions for diagnosis prediction in healthcare.

BMC medical informatics and decision making
BACKGROUND: Diagnosis aims to predict the future health status of patients according to their historical electronic health records (EHR), which is an important yet challenging task in healthcare informatics. Existing diagnosis prediction approaches m...

Representation learning for clinical time series prediction tasks in electronic health records.

BMC medical informatics and decision making
BACKGROUND: Electronic health records (EHRs) provide possibilities to improve patient care and facilitate clinical research. However, there are many challenges faced by the applications of EHRs, such as temporality, high dimensionality, sparseness, n...

Fundamentals in Artificial Intelligence for Vascular Surgeons.

Annals of vascular surgery
Artificial intelligence (AI) corresponds to a broad discipline that aims to design systems, which display properties of human intelligence. While it has led to many advances and applications in daily life, its introduction in medicine is still in its...

A forecasting model approach of sustainable electricity management by developing adaptive neuro-fuzzy inference system.

Environmental science and pollution research international
With an exponential industrial growth, an accurate demand forecasting of energy is of prime importance for strategic decision-making and new power policies regarding generation and distribution in the power sector. This is a great impediment in econo...

Development and validation of a risk prediction model to diagnose Barrett's oesophagus (MARK-BE): a case-control machine learning approach.

The Lancet. Digital health
BACKGROUND: Screening for Barrett's Oesophagus (BE) relies on endoscopy which is invasive and has a low yield. This study aimed to develop and externally validate a simple symptom and risk-factor questionnaire to screen for patients with BE.

Evolving multilayer perceptron, and factorial design for modelling and optimization of dye decomposition by bio-synthetized nano CdS-diatomite composite.

Environmental research
Design of experiment and hybrid genetic algorithm optimized multilayer perceptron (GA-MLP) artificial neural network have been employed to model and predict dye decomposition capacity of the biologically synthesized nano CdS diatomite composite. Impa...