|
|
|
|
|
Rejath Jose, Faiz Syed, Anvin Thomas and Milan Toma
The advancement of machine learning in healthcare offers significant potential for enhancing disease prediction and management. This study harnesses the PyCaret library?a Python-based machine learning toolkit?to construct and refine predictive models for...
ver más
|
|
|
|
|
|
|
|
|
Nirmal Acharya, Padmaja Kar, Mustafa Ally and Jeffrey Soar
Significant clinical overlap exists between mental health and substance use disorders, especially among women. The purpose of this research is to leverage an AutoML (Automated Machine Learning) interface to predict and distinguish co-occurring mental hea...
ver más
|
|
|
|
|
|
|
|
|
Ahmed Skhiri, Ali Ferhi, Anis Bousselmi, Slaheddine Khlifi and Mohamed A. Mattar
A correct determination of irrigation water requirements necessitates an adequate estimation of reference evapotranspiration (ETo). In this study, monthly ETo is estimated using artificial neural network (ANN) models. Eleven combinations of long-term ave...
ver más
|
|
|
|
|
|
|
|
|
Rui P. R. Nogueira, Rui Melicio, Duarte Valério and Luís F. F. M. Santos
This paper proposes a model capable of predicting fatal occurrences in aviation events such as accidents and incidents, using as inputs the human factors that contributed to each incident, together with information about the flight. This is important bec...
ver más
|
|
|
|
|
|
|
|
|
Kerim Kiliç and Jose M. Sallan
In modern business, Artificial Intelligence (AI) and Machine Learning (ML) have affected strategy and decision-making positively in the form of predictive modeling. This study aims to use ML and AI to predict arrival flight delays in the United States ai...
ver más
|
|
|
|