A Logic-Based Framework Leveraging Neural Networks for Studying the Evolution of Neurological Disorders

Abstract

Deductive formalisms have been strongly developed in recent years; among them, answer set programming (ASP) gained some momentum and has been lately fruitfully employed in many real-world scenarios. Nonetheless, in spite of a large number of success stories in relevant application areas, and even in industrial contexts, deductive reasoning cannot be considered the ultimate, comprehensive solution to artificial intelligence; indeed, in several contexts, other approaches result to be more useful. Typical bioinformatics tasks, for instance classification, are currently carried out mostly by machine learning (ML)-based solutions. In this paper, we focus on the relatively new problem of analyzing the evolution of neurological disorders. In this context, ML approaches already demonstrated to be a viable solution for classification tasks; here, we show how ASP can play a relevant role in the brain evolution simulation task. In particular, we propose a general and extensible framework to support physicians Theory and Practice of Logic Programming 81 and researchers at understanding the complex mechanisms underlying neurological disorders. The framework relies on a combined use of ML and ASP, and is general enough to be applied in several other application scenarios, which are outlined in the paper.

Meet the Medicines—A Crowdsourced Approach to Collecting and Communicating Information about Essential Medicines Online

“…Attempts at using unsupervised and semi-supervised machine-learning methods to categorize Tweets on mental health, showed firsthand that there are challenges in quantifying and categorizing unstructured data [38]. AI based on supervised machine learning is more successful in this area and has been used to identify new patterns, for example, in the evolution of neurological disorders [39]. Ultimately, the role and opportunity of AI in research relies on humans working with and understanding it.…”

Task Assignment Optimization in Multi-UAV-Assisted WSNs Considering Energy Budget and Sensor Distribution Characteristics

“…However, the features of the sensors can be divided into more types. For example, the logic-based framework proposed in [ 32 ] can be extended and applied to the construction of WSNs. Building the characteristics of sensor networks in a manner that is more in line with the application of specific scenarios will be studied and discussed in the next step.…”

How Dramatic Events Can Affect Emotionality in Social Posting: The Impact of COVID-19 on Reddit

“…The SemEval shared task also provides a data set with binary labels, in order to evaluate the performance of an emotion detection system via accuracy, precision, recall, F1score and other classical similar measures exploited in the literature [44]. Again, we applied our method to this test set in a straightforward way, labeling a tweet with an emotion every time the score computed with the NRC lexicon for that emotion was greater than a threshold of 0.25.…”