Artificial Intelligence to rapid diagnose Cystic Fibrosis

In this short assay we shall discuss a couple of papers previously published. The first paper was published Titus Slavici and Bogdan Almajan in the Journal of Rehabilitation Medicine. The first review was published by Titus Slavici and Bogdan Almajan in the Journal of Rehabilitation Medicine. The objective of this study is to construct an application with which it will be possible to determine the most effective type of physiotherapy exercise for improving the health state of an individual with Cystic Fibrosiss (CF). The second paper was published by Eva J. Zuckera, Zachary A. Barnesb, et al, in the Journal of Cystic Fibrosis. This study aimed to evaluate the hypothesis that a DCNN model could facilitate automated Brasfield scoring of chest radiographs (CXRs) for patients with CF, performing similarly to a pediatric radiologist.

Taking into account what the previous papers explained, the authors have in common that they have developed an AI model to apply to CF in order to improve the health of the patients that suffer from this disease. The authors of the first paper have developed an ANN model to predict the most suitable physiotherapy exercise for each patient, whereas the authors of the second paper have developed a DCNN model that can predict Brasfield scoring of CXRs for patients. Although the models used are different, both of them are focused on AI.

I personally think that the two papers are complementary to each other despite the aim of each study is not the same, because if you can first monitor the respiratory disease in the individual, you have more information about it and consequently you will predict a more appropriate physiotherapy exercise.

In conclusion, in my opinion, AI is a very useful instrument that may help in the quality of medical services. Also, considering that fewer experimental processes are needed, the amount of money utilized will be lower.